Overview

Dataset statistics

Number of variables200
Number of observations3417
Missing cells5454
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 MiB
Average record size in memory1.7 KiB

Variable types

Text2
Boolean45
Categorical153

Alerts

is_current_customer has constant value ""Constant
is_arr_over_12k has constant value ""Constant
company_revenue_bucket is highly overall correlated with country_top_Missing and 8 other fieldsHigh correlation
country_top is highly overall correlated with country_top_AU and 12 other fieldsHigh correlation
country_top_AU is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_BR is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_CA is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_DE is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_FR is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_GB is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_IN is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_Missing is highly overall correlated with company_revenue_bucket and 3 other fieldsHigh correlation
country_top_NL is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_Other is highly overall correlated with country_top and 1 other fieldsHigh correlation
country_top_US is highly overall correlated with country_top and 3 other fieldsHigh correlation
crossbeam_product10_customer is highly overall correlated with crossbeam_product11_customer and 22 other fieldsHigh correlation
crossbeam_product11_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product12_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product13_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product14_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product15_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product16_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product17_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product18_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product19_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product1_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product20_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product21_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product22_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product23_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product2_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product3_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product4_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product5_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product6_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product7_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product8_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
crossbeam_product9_customer is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
dnb_founded_time_grouped is highly overall correlated with country_top_Missing and 4 other fieldsHigh correlation
founded_After 2000 is highly overall correlated with dnb_founded_time_grouped and 1 other fieldsHigh correlation
founded_Before 2000 is highly overall correlated with dnb_founded_time_groupedHigh correlation
founded_nan is highly overall correlated with dnb_founded_time_grouped and 1 other fieldsHigh correlation
has_crossbeam_data is highly overall correlated with crossbeam_product10_customer and 22 other fieldsHigh correlation
has_hg_data is highly overall correlated with hg_product_100 and 122 other fieldsHigh correlation
hg_product_100 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_101 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_102 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_103 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_104 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_105 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_106 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_107 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_108 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_109 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_110 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_111 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_112 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_113 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_114 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_115 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_116 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_117 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_118 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_119 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_120 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_121 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_122 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_123 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_124 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_125 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_126 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_127 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_128 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_129 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_130 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_131 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_132 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_133 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_134 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_135 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_136 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_137 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_138 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_139 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_140 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_141 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_142 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_143 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_144 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_145 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_146 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_147 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_148 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_27 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_28 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_29 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_30 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_31 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_32 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_33 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_34 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_35 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_36 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_37 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_38 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_39 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_40 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_41 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_42 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_43 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_44 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_45 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_46 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_47 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_48 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_49 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_50 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_51 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_52 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_53 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_54 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_55 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_56 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_57 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_58 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_59 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_60 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_61 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_62 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_63 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_64 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_65 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_66 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_67 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_68 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_69 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_70 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_71 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_72 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_73 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_74 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_75 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_76 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_77 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_78 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_79 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_80 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_81 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_82 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_83 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_84 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_85 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_86 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_87 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_88 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_89 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_90 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_91 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_92 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_93 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_94 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_95 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_96 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_97 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_98 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
hg_product_99 is highly overall correlated with has_hg_data and 122 other fieldsHigh correlation
industry_1. Tech - Computer systems design and related services is highly overall correlated with industry_groupedHigh correlation
industry_2. Tech - Software Publisher is highly overall correlated with industry_groupedHigh correlation
industry_3. Finance is highly overall correlated with industry_groupedHigh correlation
industry_4. Consulting is highly overall correlated with industry_groupedHigh correlation
industry_5. Retail is highly overall correlated with industry_groupedHigh correlation
industry_6. Manufacturing is highly overall correlated with industry_groupedHigh correlation
industry_7. Wholesale Trade is highly overall correlated with industry_groupedHigh correlation
industry_8. Healthcare is highly overall correlated with industry_groupedHigh correlation
industry_9. Other is highly overall correlated with industry_groupedHigh correlation
industry_grouped is highly overall correlated with industry_1. Tech - Computer systems design and related services and 9 other fieldsHigh correlation
industry_nan is highly overall correlated with company_revenue_bucket and 2 other fieldsHigh correlation
revenue_Over 10B is highly overall correlated with company_revenue_bucketHigh correlation
revenue_Under 100M is highly overall correlated with company_revenue_bucketHigh correlation
revenue_Under 10B is highly overall correlated with company_revenue_bucketHigh correlation
revenue_Under 10M is highly overall correlated with company_revenue_bucketHigh correlation
revenue_Under 1B is highly overall correlated with company_revenue_bucket and 1 other fieldsHigh correlation
revenue_Under 1M is highly overall correlated with company_revenue_bucketHigh correlation
revenue_nan is highly overall correlated with company_revenue_bucket and 124 other fieldsHigh correlation
state is highly overall correlated with country_top and 23 other fieldsHigh correlation
state_top is highly overall correlated with country_top_US and 12 other fieldsHigh correlation
state_top_CA is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_CO is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_FL is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_GA is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_IL is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_MA is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_Missing is highly overall correlated with country_top and 3 other fieldsHigh correlation
state_top_NY is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_Other is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_TX is highly overall correlated with state and 1 other fieldsHigh correlation
state_top_WA is highly overall correlated with state and 1 other fieldsHigh correlation
has_crossbeam_data is highly imbalanced (84.0%)Imbalance
crossbeam_product1_customer is highly imbalanced (84.6%)Imbalance
crossbeam_product2_customer is highly imbalanced (80.7%)Imbalance
crossbeam_product3_customer is highly imbalanced (76.7%)Imbalance
crossbeam_product4_customer is highly imbalanced (86.4%)Imbalance
crossbeam_product5_customer is highly imbalanced (81.9%)Imbalance
crossbeam_product6_customer is highly imbalanced (57.0%)Imbalance
crossbeam_product7_customer is highly imbalanced (83.9%)Imbalance
crossbeam_product8_customer is highly imbalanced (60.2%)Imbalance
crossbeam_product9_customer is highly imbalanced (88.3%)Imbalance
crossbeam_product10_customer is highly imbalanced (67.2%)Imbalance
crossbeam_product11_customer is highly imbalanced (67.9%)Imbalance
crossbeam_product12_customer is highly imbalanced (76.5%)Imbalance
crossbeam_product13_customer is highly imbalanced (87.4%)Imbalance
crossbeam_product14_customer is highly imbalanced (82.6%)Imbalance
crossbeam_product15_customer is highly imbalanced (60.8%)Imbalance
crossbeam_product16_customer is highly imbalanced (78.0%)Imbalance
crossbeam_product17_customer is highly imbalanced (83.3%)Imbalance
crossbeam_product18_customer is highly imbalanced (71.2%)Imbalance
crossbeam_product19_customer is highly imbalanced (72.5%)Imbalance
crossbeam_product21_customer is highly imbalanced (71.6%)Imbalance
crossbeam_product22_customer is highly imbalanced (84.3%)Imbalance
country_top_AU is highly imbalanced (79.8%)Imbalance
country_top_BR is highly imbalanced (94.8%)Imbalance
country_top_CA is highly imbalanced (78.2%)Imbalance
country_top_DE is highly imbalanced (82.9%)Imbalance
country_top_FR is highly imbalanced (86.6%)Imbalance
country_top_GB is highly imbalanced (60.5%)Imbalance
country_top_IN is highly imbalanced (94.2%)Imbalance
country_top_Missing is highly imbalanced (98.4%)Imbalance
country_top_NL is highly imbalanced (89.0%)Imbalance
country_top_Other is highly imbalanced (50.7%)Imbalance
state_top_CO is highly imbalanced (86.4%)Imbalance
state_top_FL is highly imbalanced (85.3%)Imbalance
state_top_GA is highly imbalanced (89.9%)Imbalance
state_top_IL is highly imbalanced (81.7%)Imbalance
state_top_MA is highly imbalanced (77.1%)Imbalance
state_top_TX is highly imbalanced (75.1%)Imbalance
state_top_WA is highly imbalanced (86.4%)Imbalance
industry_2. Tech - Software Publisher is highly imbalanced (69.0%)Imbalance
industry_3. Finance is highly imbalanced (52.9%)Imbalance
industry_4. Consulting is highly imbalanced (77.1%)Imbalance
industry_5. Retail is highly imbalanced (60.5%)Imbalance
industry_6. Manufacturing is highly imbalanced (57.3%)Imbalance
industry_7. Wholesale Trade is highly imbalanced (72.7%)Imbalance
industry_8. Healthcare is highly imbalanced (76.0%)Imbalance
industry_nan is highly imbalanced (80.1%)Imbalance
revenue_Over 10B is highly imbalanced (81.5%)Imbalance
revenue_Under 100M is highly imbalanced (69.7%)Imbalance
revenue_Under 10B is highly imbalanced (61.3%)Imbalance
revenue_Under 10M is highly imbalanced (91.2%)Imbalance
revenue_Under 1M is highly imbalanced (97.6%)Imbalance
company_revenue_bucket has 2385 (69.8%) missing valuesMissing
state has 1133 (33.2%) missing valuesMissing
industry_grouped has 106 (3.1%) missing valuesMissing
dnb_founded_time_grouped has 1825 (53.4%) missing valuesMissing
account_id has unique valuesUnique

Reproduction

Analysis started2023-12-31 21:49:16.775296
Analysis finished2023-12-31 21:51:01.347125
Duration1 minute and 44.57 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

account_id
Text

UNIQUE 

Distinct3417
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size277.0 KiB
2023-12-31T13:51:01.543213image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters61506
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3417 ?
Unique (%)100.0%

Sample

1st row0011G00000tL14IQAS
2nd row0011G00000gY7jaQAC
3rd row0011G00000kx074QAA
4th row0011G00000pPUQ1QAO
5th row0013700000YPwoTAAT
ValueCountFrequency (%)
0011g00000tl14iqas 1
 
< 0.1%
0011g00000oxbdaqaq 1
 
< 0.1%
0011g00000ny6aiqak 1
 
< 0.1%
0011g00000kx074qaa 1
 
< 0.1%
0011g00000ppuq1qao 1
 
< 0.1%
0013700000ypwotaat 1
 
< 0.1%
0011g00000kwwqdqai 1
 
< 0.1%
0011g00000uns5zqaa 1
 
< 0.1%
0011g00000ugvn9qaa 1
 
< 0.1%
0011g00000kbsccqak 1
 
< 0.1%
Other values (3407) 3407
99.7%
2023-12-31T13:51:01.930655image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24276
39.5%
1 6646
 
10.8%
A 4376
 
7.1%
G 3269
 
5.3%
Q 3255
 
5.3%
3 757
 
1.2%
7 746
 
1.2%
g 744
 
1.2%
Y 739
 
1.2%
C 628
 
1.0%
Other values (52) 16070
26.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34178
55.6%
Uppercase Letter 19101
31.1%
Lowercase Letter 8227
 
13.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 4376
22.9%
G 3269
17.1%
Q 3255
17.0%
Y 739
 
3.9%
C 628
 
3.3%
I 489
 
2.6%
K 488
 
2.6%
S 478
 
2.5%
M 426
 
2.2%
Z 397
 
2.1%
Other values (16) 4556
23.9%
Lowercase Letter
ValueCountFrequency (%)
g 744
 
9.0%
n 571
 
6.9%
k 501
 
6.1%
f 461
 
5.6%
w 455
 
5.5%
h 440
 
5.3%
e 387
 
4.7%
q 370
 
4.5%
u 338
 
4.1%
c 303
 
3.7%
Other values (16) 3657
44.5%
Decimal Number
ValueCountFrequency (%)
0 24276
71.0%
1 6646
 
19.4%
3 757
 
2.2%
7 746
 
2.2%
4 348
 
1.0%
9 333
 
1.0%
2 328
 
1.0%
8 301
 
0.9%
5 232
 
0.7%
6 211
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 34178
55.6%
Latin 27328
44.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 4376
 
16.0%
G 3269
 
12.0%
Q 3255
 
11.9%
g 744
 
2.7%
Y 739
 
2.7%
C 628
 
2.3%
n 571
 
2.1%
k 501
 
1.8%
I 489
 
1.8%
K 488
 
1.8%
Other values (42) 12268
44.9%
Common
ValueCountFrequency (%)
0 24276
71.0%
1 6646
 
19.4%
3 757
 
2.2%
7 746
 
2.2%
4 348
 
1.0%
9 333
 
1.0%
2 328
 
1.0%
8 301
 
0.9%
5 232
 
0.7%
6 211
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24276
39.5%
1 6646
 
10.8%
A 4376
 
7.1%
G 3269
 
5.3%
Q 3255
 
5.3%
3 757
 
1.2%
7 746
 
1.2%
g 744
 
1.2%
Y 739
 
1.2%
C 628
 
1.0%
Other values (52) 16070
26.1%

is_current_customer
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
True
3417 
ValueCountFrequency (%)
True 3417
100.0%
2023-12-31T13:51:02.081131image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

is_self_service
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.4 KiB
-1.0
2578 
1.0
839 

Length

Max length4
Median length4
Mean length3.754463
Min length3

Characters and Unicode

Total characters12829
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row-1.0
3rd row-1.0
4th row-1.0
5th row1.0

Common Values

ValueCountFrequency (%)
-1.0 2578
75.4%
1.0 839
 
24.6%

Length

2023-12-31T13:51:02.197339image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:02.303416image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3417
100.0%

Most occurring characters

ValueCountFrequency (%)
1 3417
26.6%
. 3417
26.6%
0 3417
26.6%
- 2578
20.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
53.3%
Other Punctuation 3417
26.6%
Dash Punctuation 2578
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3417
50.0%
0 3417
50.0%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2578
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12829
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3417
26.6%
. 3417
26.6%
0 3417
26.6%
- 2578
20.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3417
26.6%
. 3417
26.6%
0 3417
26.6%
- 2578
20.1%

is_arr_over_12k
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size226.9 KiB
1.0
3417 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters10251
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 3417
100.0%

Length

2023-12-31T13:51:02.419652image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:02.526460image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3417
100.0%

Most occurring characters

ValueCountFrequency (%)
1 3417
33.3%
. 3417
33.3%
0 3417
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
66.7%
Other Punctuation 3417
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3417
50.0%
0 3417
50.0%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3417
33.3%
. 3417
33.3%
0 3417
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3417
33.3%
. 3417
33.3%
0 3417
33.3%

company_revenue_bucket
Categorical

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)0.6%
Missing2385
Missing (%)69.8%
Memory size241.9 KiB
Under 1B
447 
Under 10B
259 
Under 100M
184 
Over 10B
96 
Under 10M
 
38

Length

Max length10
Median length8
Mean length8.6443798
Min length8

Characters and Unicode

Total characters8921
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnder 100M
2nd rowUnder 1B
3rd rowUnder 1B
4th rowOver 10B
5th rowUnder 1B

Common Values

ValueCountFrequency (%)
Under 1B 447
 
13.1%
Under 10B 259
 
7.6%
Under 100M 184
 
5.4%
Over 10B 96
 
2.8%
Under 10M 38
 
1.1%
Under 1M 8
 
0.2%
(Missing) 2385
69.8%

Length

2023-12-31T13:51:02.649251image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:02.791014image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
under 936
45.3%
1b 447
21.7%
10b 355
 
17.2%
100m 184
 
8.9%
over 96
 
4.7%
10m 38
 
1.8%
1m 8
 
0.4%

Most occurring characters

ValueCountFrequency (%)
e 1032
11.6%
r 1032
11.6%
1032
11.6%
1 1032
11.6%
U 936
10.5%
n 936
10.5%
d 936
10.5%
B 802
9.0%
0 761
8.5%
M 230
 
2.6%
Other values (2) 192
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4032
45.2%
Uppercase Letter 2064
23.1%
Decimal Number 1793
20.1%
Space Separator 1032
 
11.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1032
25.6%
r 1032
25.6%
n 936
23.2%
d 936
23.2%
v 96
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
U 936
45.3%
B 802
38.9%
M 230
 
11.1%
O 96
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 1032
57.6%
0 761
42.4%
Space Separator
ValueCountFrequency (%)
1032
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6096
68.3%
Common 2825
31.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1032
16.9%
r 1032
16.9%
U 936
15.4%
n 936
15.4%
d 936
15.4%
B 802
13.2%
M 230
 
3.8%
O 96
 
1.6%
v 96
 
1.6%
Common
ValueCountFrequency (%)
1032
36.5%
1 1032
36.5%
0 761
26.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1032
11.6%
r 1032
11.6%
1032
11.6%
1 1032
11.6%
U 936
10.5%
n 936
10.5%
d 936
10.5%
B 802
9.0%
0 761
8.5%
M 230
 
2.6%
Other values (2) 192
 
2.2%
Distinct61
Distinct (%)1.8%
Missing5
Missing (%)0.1%
Memory size223.4 KiB
2023-12-31T13:51:02.999047image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters6824
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.5%

Sample

1st rowAG
2nd rowFR
3rd rowUS
4th rowUS
5th rowDE
ValueCountFrequency (%)
us 2307
67.6%
gb 266
 
7.8%
ca 119
 
3.5%
au 108
 
3.2%
de 87
 
2.5%
fr 64
 
1.9%
nl 50
 
1.5%
se 29
 
0.8%
il 29
 
0.8%
in 23
 
0.7%
Other values (51) 330
 
9.7%
2023-12-31T13:51:03.322017image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 2418
35.4%
S 2385
35.0%
B 305
 
4.5%
G 299
 
4.4%
A 260
 
3.8%
E 182
 
2.7%
C 161
 
2.4%
N 118
 
1.7%
D 103
 
1.5%
R 96
 
1.4%
Other values (15) 497
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6824
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 2418
35.4%
S 2385
35.0%
B 305
 
4.5%
G 299
 
4.4%
A 260
 
3.8%
E 182
 
2.7%
C 161
 
2.4%
N 118
 
1.7%
D 103
 
1.5%
R 96
 
1.4%
Other values (15) 497
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 6824
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 2418
35.4%
S 2385
35.0%
B 305
 
4.5%
G 299
 
4.4%
A 260
 
3.8%
E 182
 
2.7%
C 161
 
2.4%
N 118
 
1.7%
D 103
 
1.5%
R 96
 
1.4%
Other values (15) 497
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 2418
35.4%
S 2385
35.0%
B 305
 
4.5%
G 299
 
4.4%
A 260
 
3.8%
E 182
 
2.7%
C 161
 
2.4%
N 118
 
1.7%
D 103
 
1.5%
R 96
 
1.4%
Other values (15) 497
 
7.3%

state
Categorical

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)2.0%
Missing1133
Missing (%)33.2%
Memory size229.1 KiB
CA
708 
NY
380 
TX
142 
MA
127 
IL
95 
Other values (41)
832 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4568
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st rowCA
2nd rowNE
3rd rowMI
4th rowNY
5th rowPA

Common Values

ValueCountFrequency (%)
CA 708
20.7%
NY 380
 
11.1%
TX 142
 
4.2%
MA 127
 
3.7%
IL 95
 
2.8%
FL 72
 
2.1%
WA 65
 
1.9%
CO 65
 
1.9%
UT 56
 
1.6%
GA 45
 
1.3%
Other values (36) 529
15.5%
(Missing) 1133
33.2%

Length

2023-12-31T13:51:03.491164image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca 708
31.0%
ny 380
16.6%
tx 142
 
6.2%
ma 127
 
5.6%
il 95
 
4.2%
fl 72
 
3.2%
wa 65
 
2.8%
co 65
 
2.8%
ut 56
 
2.5%
ga 45
 
2.0%
Other values (36) 529
23.2%

Most occurring characters

ValueCountFrequency (%)
A 1069
23.4%
C 829
18.1%
N 547
12.0%
Y 385
 
8.4%
T 242
 
5.3%
M 234
 
5.1%
L 179
 
3.9%
I 168
 
3.7%
O 163
 
3.6%
X 142
 
3.1%
Other values (14) 610
13.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4568
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1069
23.4%
C 829
18.1%
N 547
12.0%
Y 385
 
8.4%
T 242
 
5.3%
M 234
 
5.1%
L 179
 
3.9%
I 168
 
3.7%
O 163
 
3.6%
X 142
 
3.1%
Other values (14) 610
13.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 4568
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1069
23.4%
C 829
18.1%
N 547
12.0%
Y 385
 
8.4%
T 242
 
5.3%
M 234
 
5.1%
L 179
 
3.9%
I 168
 
3.7%
O 163
 
3.6%
X 142
 
3.1%
Other values (14) 610
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1069
23.4%
C 829
18.1%
N 547
12.0%
Y 385
 
8.4%
T 242
 
5.3%
M 234
 
5.1%
L 179
 
3.9%
I 168
 
3.7%
O 163
 
3.6%
X 142
 
3.1%
Other values (14) 610
13.4%

industry_grouped
Categorical

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)0.3%
Missing106
Missing (%)3.1%
Memory size276.9 KiB
9. Other
1265 
1. Tech - Computer systems design and related services
526 
3. Finance
344 
6. Manufacturing
298 
5. Retail
266 
Other values (4)
612 

Length

Max length54
Median length28
Mean length18.342495
Min length8

Characters and Unicode

Total characters60732
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9. Other
2nd row2. Tech - Software Publisher
3rd row3. Finance
4th row1. Tech - Computer systems design and related services
5th row1. Tech - Computer systems design and related services

Common Values

ValueCountFrequency (%)
9. Other 1265
37.0%
1. Tech - Computer systems design and related services 526
15.4%
3. Finance 344
 
10.1%
6. Manufacturing 298
 
8.7%
5. Retail 266
 
7.8%
2. Tech - Software Publisher 190
 
5.6%
7. Wholesale Trade 160
 
4.7%
8. Healthcare 135
 
4.0%
4. Consulting 127
 
3.7%
(Missing) 106
 
3.1%

Length

2023-12-31T13:51:03.670307image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:04.068374image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
9 1265
 
11.5%
other 1265
 
11.5%
tech 716
 
6.5%
716
 
6.5%
1 526
 
4.8%
computer 526
 
4.8%
systems 526
 
4.8%
design 526
 
4.8%
and 526
 
4.8%
related 526
 
4.8%
Other values (17) 3916
35.5%

Most occurring characters

ValueCountFrequency (%)
7723
 
12.7%
e 7403
 
12.2%
t 3859
 
6.4%
r 3816
 
6.3%
s 3633
 
6.0%
. 3311
 
5.5%
a 3038
 
5.0%
n 2590
 
4.3%
h 2466
 
4.1%
i 2277
 
3.7%
Other values (33) 20616
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41294
68.0%
Space Separator 7723
 
12.7%
Uppercase Letter 4377
 
7.2%
Other Punctuation 3311
 
5.5%
Decimal Number 3311
 
5.5%
Dash Punctuation 716
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7403
17.9%
t 3859
9.3%
r 3816
9.2%
s 3633
8.8%
a 3038
 
7.4%
n 2590
 
6.3%
h 2466
 
6.0%
i 2277
 
5.5%
c 2019
 
4.9%
d 1738
 
4.2%
Other values (11) 8455
20.5%
Uppercase Letter
ValueCountFrequency (%)
O 1265
28.9%
T 876
20.0%
C 653
14.9%
F 344
 
7.9%
M 298
 
6.8%
R 266
 
6.1%
S 190
 
4.3%
P 190
 
4.3%
W 160
 
3.7%
H 135
 
3.1%
Decimal Number
ValueCountFrequency (%)
9 1265
38.2%
1 526
15.9%
3 344
 
10.4%
6 298
 
9.0%
5 266
 
8.0%
2 190
 
5.7%
7 160
 
4.8%
8 135
 
4.1%
4 127
 
3.8%
Space Separator
ValueCountFrequency (%)
7723
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 716
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45671
75.2%
Common 15061
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7403
16.2%
t 3859
 
8.4%
r 3816
 
8.4%
s 3633
 
8.0%
a 3038
 
6.7%
n 2590
 
5.7%
h 2466
 
5.4%
i 2277
 
5.0%
c 2019
 
4.4%
d 1738
 
3.8%
Other values (21) 12832
28.1%
Common
ValueCountFrequency (%)
7723
51.3%
. 3311
22.0%
9 1265
 
8.4%
- 716
 
4.8%
1 526
 
3.5%
3 344
 
2.3%
6 298
 
2.0%
5 266
 
1.8%
2 190
 
1.3%
7 160
 
1.1%
Other values (2) 262
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7723
 
12.7%
e 7403
 
12.2%
t 3859
 
6.4%
r 3816
 
6.3%
s 3633
 
6.0%
. 3311
 
5.5%
a 3038
 
5.0%
n 2590
 
4.3%
h 2466
 
4.1%
i 2277
 
3.7%
Other values (33) 20616
33.9%

has_crossbeam_data
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
True
3337 
False
 
80
ValueCountFrequency (%)
True 3337
97.7%
False 80
 
2.3%
2023-12-31T13:51:04.237236image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

crossbeam_product1_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3301 
0.0
 
78
1.0
 
38

Length

Max length4
Median length4
Mean length3.9660521
Min length3

Characters and Unicode

Total characters13552
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3301
96.6%
0.0 78
 
2.3%
1.0 38
 
1.1%

Length

2023-12-31T13:51:04.366131image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:04.481431image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3301
24.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.4%
Other Punctuation 3417
25.2%
Dash Punctuation 3301
24.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3301
24.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3301
24.4%

crossbeam_product2_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3266 
0.0
 
78
1.0
 
73

Length

Max length4
Median length4
Mean length3.9558092
Min length3

Characters and Unicode

Total characters13517
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3266
95.6%
0.0 78
 
2.3%
1.0 73
 
2.1%

Length

2023-12-31T13:51:04.602986image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:04.717713image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.7%
- 3266
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.6%
Other Punctuation 3417
25.3%
Dash Punctuation 3266
24.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.7%
- 3266
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.7%
- 3266
24.2%

crossbeam_product3_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3223 
1.0
 
116
0.0
 
78

Length

Max length4
Median length4
Mean length3.9432251
Min length3

Characters and Unicode

Total characters13474
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3223
94.3%
1.0 116
 
3.4%
0.0 78
 
2.3%

Length

2023-12-31T13:51:04.860570image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:05.004586image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3223
23.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.7%
Other Punctuation 3417
25.4%
Dash Punctuation 3223
23.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13474
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3223
23.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3223
23.9%

crossbeam_product4_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3316 
0.0
 
78
1.0
 
23

Length

Max length4
Median length4
Mean length3.9704419
Min length3

Characters and Unicode

Total characters13567
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3316
97.0%
0.0 78
 
2.3%
1.0 23
 
0.7%

Length

2023-12-31T13:51:05.162695image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:05.308574image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3316
24.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.4%
Other Punctuation 3417
25.2%
Dash Punctuation 3316
24.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3316
24.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3316
24.4%

crossbeam_product5_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3277 
0.0
 
78
1.0
 
62

Length

Max length4
Median length4
Mean length3.9590284
Min length3

Characters and Unicode

Total characters13528
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3277
95.9%
0.0 78
 
2.3%
1.0 62
 
1.8%

Length

2023-12-31T13:51:05.454401image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:05.594125image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.3%
1 3339
24.7%
- 3277
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.5%
Other Punctuation 3417
25.3%
Dash Punctuation 3277
24.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3277
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13528
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.3%
1 3339
24.7%
- 3277
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.3%
1 3339
24.7%
- 3277
24.2%

crossbeam_product6_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.8 KiB
-1.0
2929 
1.0
410 
0.0
 
78

Length

Max length4
Median length4
Mean length3.8571847
Min length3

Characters and Unicode

Total characters13180
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 2929
85.7%
1.0 410
 
12.0%
0.0 78
 
2.3%

Length

2023-12-31T13:51:05.717410image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:05.829060image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.5%
. 3417
25.9%
1 3339
25.3%
- 2929
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.9%
Other Punctuation 3417
25.9%
Dash Punctuation 2929
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2929
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.5%
. 3417
25.9%
1 3339
25.3%
- 2929
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.5%
. 3417
25.9%
1 3339
25.3%
- 2929
22.2%

crossbeam_product7_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3295 
0.0
 
78
1.0
 
44

Length

Max length4
Median length4
Mean length3.9642962
Min length3

Characters and Unicode

Total characters13546
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3295
96.4%
0.0 78
 
2.3%
1.0 44
 
1.3%

Length

2023-12-31T13:51:05.955286image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:06.107046image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3295
24.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.5%
Other Punctuation 3417
25.2%
Dash Punctuation 3295
24.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3295
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3295
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3295
24.3%

crossbeam_product8_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.8 KiB
-1.0
2988 
1.0
351 
0.0
 
78

Length

Max length4
Median length4
Mean length3.8744513
Min length3

Characters and Unicode

Total characters13239
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 2988
87.4%
1.0 351
 
10.3%
0.0 78
 
2.3%

Length

2023-12-31T13:51:06.257546image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:06.397392image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2988
22.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.6%
Other Punctuation 3417
25.8%
Dash Punctuation 2988
22.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13239
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2988
22.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2988
22.6%

crossbeam_product9_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.2 KiB
-1.0
3329 
0.0
 
78
1.0
 
10

Length

Max length4
Median length4
Mean length3.9742464
Min length3

Characters and Unicode

Total characters13580
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3329
97.4%
0.0 78
 
2.3%
1.0 10
 
0.3%

Length

2023-12-31T13:51:06.519524image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:06.627750image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3329
24.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.3%
Other Punctuation 3417
25.2%
Dash Punctuation 3329
24.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3329
24.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3329
24.5%

crossbeam_product10_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.9 KiB
-1.0
3100 
1.0
 
239
0.0
 
78

Length

Max length4
Median length4
Mean length3.9072286
Min length3

Characters and Unicode

Total characters13351
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3100
90.7%
1.0 239
 
7.0%
0.0 78
 
2.3%

Length

2023-12-31T13:51:06.741380image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:06.850256image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3100
23.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.2%
Other Punctuation 3417
25.6%
Dash Punctuation 3100
23.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3100
23.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3100
23.2%

crossbeam_product11_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.9 KiB
-1.0
3110 
1.0
 
229
0.0
 
78

Length

Max length4
Median length4
Mean length3.9101551
Min length3

Characters and Unicode

Total characters13361
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3110
91.0%
1.0 229
 
6.7%
0.0 78
 
2.3%

Length

2023-12-31T13:51:06.967128image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:07.076853image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3110
23.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.1%
Other Punctuation 3417
25.6%
Dash Punctuation 3110
23.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3110
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.2%
. 3417
25.6%
1 3339
25.0%
- 3110
23.3%

crossbeam_product12_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3221 
1.0
 
118
0.0
 
78

Length

Max length4
Median length4
Mean length3.9426397
Min length3

Characters and Unicode

Total characters13472
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3221
94.3%
1.0 118
 
3.5%
0.0 78
 
2.3%

Length

2023-12-31T13:51:07.209824image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:07.315170image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3221
23.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.7%
Other Punctuation 3417
25.4%
Dash Punctuation 3221
23.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3221
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13472
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3221
23.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.4%
1 3339
24.8%
- 3221
23.9%

crossbeam_product13_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.2 KiB
-1.0
3323 
0.0
 
78
1.0
 
16

Length

Max length4
Median length4
Mean length3.9724905
Min length3

Characters and Unicode

Total characters13574
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3323
97.2%
0.0 78
 
2.3%
1.0 16
 
0.5%

Length

2023-12-31T13:51:07.428003image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:07.536782image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3323
24.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.3%
Other Punctuation 3417
25.2%
Dash Punctuation 3323
24.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3323
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13574
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3323
24.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.7%
. 3417
25.2%
1 3339
24.6%
- 3323
24.5%

crossbeam_product14_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3284 
0.0
 
78
1.0
 
55

Length

Max length4
Median length4
Mean length3.961077
Min length3

Characters and Unicode

Total characters13535
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3284
96.1%
0.0 78
 
2.3%
1.0 55
 
1.6%

Length

2023-12-31T13:51:07.672482image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:07.800642image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3284
24.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.5%
Other Punctuation 3417
25.2%
Dash Punctuation 3284
24.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3284
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13535
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3284
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13535
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3284
24.3%

crossbeam_product15_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.8 KiB
-1.0
2999 
1.0
340 
0.0
 
78

Length

Max length4
Median length4
Mean length3.8776705
Min length3

Characters and Unicode

Total characters13250
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 2999
87.8%
1.0 340
 
10.0%
0.0 78
 
2.3%

Length

2023-12-31T13:51:07.925470image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:08.051458image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2999
22.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.6%
Other Punctuation 3417
25.8%
Dash Punctuation 2999
22.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2999
22.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.4%
. 3417
25.8%
1 3339
25.2%
- 2999
22.6%

crossbeam_product16_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3238 
1.0
 
101
0.0
 
78

Length

Max length4
Median length4
Mean length3.9476149
Min length3

Characters and Unicode

Total characters13489
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3238
94.8%
1.0 101
 
3.0%
0.0 78
 
2.3%

Length

2023-12-31T13:51:08.183344image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:08.305069image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.8%
- 3238
24.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.7%
Other Punctuation 3417
25.3%
Dash Punctuation 3238
24.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.8%
- 3238
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.9%
. 3417
25.3%
1 3339
24.8%
- 3238
24.0%

crossbeam_product17_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3290 
0.0
 
78
1.0
 
49

Length

Max length4
Median length4
Mean length3.9628329
Min length3

Characters and Unicode

Total characters13541
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3290
96.3%
0.0 78
 
2.3%
1.0 49
 
1.4%

Length

2023-12-31T13:51:08.438085image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:08.544888image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3290
24.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.5%
Other Punctuation 3417
25.2%
Dash Punctuation 3290
24.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13541
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3290
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.7%
- 3290
24.3%

crossbeam_product18_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.0 KiB
-1.0
3156 
1.0
 
183
0.0
 
78

Length

Max length4
Median length4
Mean length3.9236172
Min length3

Characters and Unicode

Total characters13407
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3156
92.4%
1.0 183
 
5.4%
0.0 78
 
2.3%

Length

2023-12-31T13:51:08.664494image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:08.773857image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3156
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.0%
Other Punctuation 3417
25.5%
Dash Punctuation 3156
23.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3156
23.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3156
23.5%

crossbeam_product19_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.0 KiB
-1.0
3173 
1.0
 
166
0.0
 
78

Length

Max length4
Median length4
Mean length3.9285923
Min length3

Characters and Unicode

Total characters13424
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3173
92.9%
1.0 166
 
4.9%
0.0 78
 
2.3%

Length

2023-12-31T13:51:08.936163image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:09.088874image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.0%
. 3417
25.5%
1 3339
24.9%
- 3173
23.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.9%
Other Punctuation 3417
25.5%
Dash Punctuation 3173
23.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13424
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.0%
. 3417
25.5%
1 3339
24.9%
- 3173
23.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.0%
. 3417
25.5%
1 3339
24.9%
- 3173
23.6%

crossbeam_product20_customer
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.7 KiB
-1.0
1858 
1.0
1481 
0.0
 
78

Length

Max length4
Median length4
Mean length3.5437518
Min length3

Characters and Unicode

Total characters12109
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 1858
54.4%
1.0 1481
43.3%
0.0 78
 
2.3%

Length

2023-12-31T13:51:09.241503image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:09.409441image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
28.9%
. 3417
28.2%
1 3339
27.6%
- 1858
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
56.4%
Other Punctuation 3417
28.2%
Dash Punctuation 1858
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1858
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
28.9%
. 3417
28.2%
1 3339
27.6%
- 1858
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
28.9%
. 3417
28.2%
1 3339
27.6%
- 1858
15.3%

crossbeam_product21_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.0 KiB
-1.0
3161 
1.0
 
178
0.0
 
78

Length

Max length4
Median length4
Mean length3.9250805
Min length3

Characters and Unicode

Total characters13412
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3161
92.5%
1.0 178
 
5.2%
0.0 78
 
2.3%

Length

2023-12-31T13:51:09.577474image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:09.707614image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3161
23.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
51.0%
Other Punctuation 3417
25.5%
Dash Punctuation 3161
23.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13412
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3161
23.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
26.1%
. 3417
25.5%
1 3339
24.9%
- 3161
23.6%

crossbeam_product22_customer
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size230.1 KiB
-1.0
3299 
0.0
 
78
1.0
 
40

Length

Max length4
Median length4
Mean length3.9654668
Min length3

Characters and Unicode

Total characters13550
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 3299
96.5%
0.0 78
 
2.3%
1.0 40
 
1.2%

Length

2023-12-31T13:51:09.824415image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:09.930925image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3299
24.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
50.4%
Other Punctuation 3417
25.2%
Dash Punctuation 3299
24.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3299
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3299
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
25.8%
. 3417
25.2%
1 3339
24.6%
- 3299
24.3%

crossbeam_product23_customer
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size229.0 KiB
-1.0
2176 
1.0
1163 
0.0
 
78

Length

Max length4
Median length4
Mean length3.6368159
Min length3

Characters and Unicode

Total characters12427
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
-1.0 2176
63.7%
1.0 1163
34.0%
0.0 78
 
2.3%

Length

2023-12-31T13:51:10.045806image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:10.160476image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3339
97.7%
0.0 78
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3495
28.1%
. 3417
27.5%
1 3339
26.9%
- 2176
17.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
55.0%
Other Punctuation 3417
27.5%
Dash Punctuation 2176
 
17.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3495
51.1%
1 3339
48.9%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12427
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3495
28.1%
. 3417
27.5%
1 3339
26.9%
- 2176
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12427
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3495
28.1%
. 3417
27.5%
1 3339
26.9%
- 2176
17.5%

dnb_founded_time_grouped
Categorical

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing1825
Missing (%)53.4%
Memory size245.3 KiB
After 2000
1166 
Before 2000
426 

Length

Max length11
Median length10
Mean length10.267588
Min length10

Characters and Unicode

Total characters16346
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAfter 2000
2nd rowBefore 2000
3rd rowAfter 2000
4th rowAfter 2000
5th rowAfter 2000

Common Values

ValueCountFrequency (%)
After 2000 1166
34.1%
Before 2000 426
 
12.5%
(Missing) 1825
53.4%

Length

2023-12-31T13:51:10.289608image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:10.405109image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
2000 1592
50.0%
after 1166
36.6%
before 426
 
13.4%

Most occurring characters

ValueCountFrequency (%)
0 4776
29.2%
e 2018
12.3%
f 1592
 
9.7%
r 1592
 
9.7%
1592
 
9.7%
2 1592
 
9.7%
A 1166
 
7.1%
t 1166
 
7.1%
B 426
 
2.6%
o 426
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6794
41.6%
Decimal Number 6368
39.0%
Space Separator 1592
 
9.7%
Uppercase Letter 1592
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2018
29.7%
f 1592
23.4%
r 1592
23.4%
t 1166
17.2%
o 426
 
6.3%
Decimal Number
ValueCountFrequency (%)
0 4776
75.0%
2 1592
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 1166
73.2%
B 426
 
26.8%
Space Separator
ValueCountFrequency (%)
1592
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8386
51.3%
Common 7960
48.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2018
24.1%
f 1592
19.0%
r 1592
19.0%
A 1166
13.9%
t 1166
13.9%
B 426
 
5.1%
o 426
 
5.1%
Common
ValueCountFrequency (%)
0 4776
60.0%
1592
 
20.0%
2 1592
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4776
29.2%
e 2018
12.3%
f 1592
 
9.7%
r 1592
 
9.7%
1592
 
9.7%
2 1592
 
9.7%
A 1166
 
7.1%
t 1166
 
7.1%
B 426
 
2.6%
o 426
 
2.6%

has_hg_data
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2330 
True
1087 
ValueCountFrequency (%)
False 2330
68.2%
True 1087
31.8%
2023-12-31T13:51:10.502719image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

hg_product_27
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:10.615289image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:10.720992image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_28
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.7 KiB
0.0
2279 
-1.0
848 
1.0
290 

Length

Max length4
Median length3
Mean length3.2481709
Min length3

Characters and Unicode

Total characters11099
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 848
 
24.8%
1.0 290
 
8.5%

Length

2023-12-31T13:51:10.837325image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:10.951837image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.6%
Other Punctuation 3417
30.8%
Dash Punctuation 848
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 848
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11099
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

hg_product_29
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1064 
1.0
 
74

Length

Max length4
Median length3
Mean length3.3113843
Min length3

Characters and Unicode

Total characters11315
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1064
31.1%
1.0 74
 
2.2%

Length

2023-12-31T13:51:11.061641image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:11.172153image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1064
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1064
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

hg_product_30
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1076 
1.0
 
62

Length

Max length4
Median length3
Mean length3.3148961
Min length3

Characters and Unicode

Total characters11327
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1076
31.5%
1.0 62
 
1.8%

Length

2023-12-31T13:51:11.289881image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:11.395453image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1076
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.2%
Dash Punctuation 1076
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1076
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1076
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1076
 
9.5%

hg_product_31
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.5 KiB
0.0
2279 
-1.0
601 
1.0
537 

Length

Max length4
Median length3
Mean length3.1758853
Min length3

Characters and Unicode

Total characters10852
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 601
 
17.6%
1.0 537
 
15.7%

Length

2023-12-31T13:51:11.507028image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:11.610995image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 601
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.0%
Other Punctuation 3417
31.5%
Dash Punctuation 601
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 601
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10852
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 601
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 601
 
5.5%

hg_product_32
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
759 
-1.0
379 

Length

Max length4
Median length3
Mean length3.110916
Min length3

Characters and Unicode

Total characters10630
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 759
 
22.2%
-1.0 379
 
11.1%

Length

2023-12-31T13:51:11.734499image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:11.856667image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.1%
1 1138
 
10.7%
- 379
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
64.3%
Other Punctuation 3417
32.1%
Dash Punctuation 379
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 379
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10630
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.1%
1 1138
 
10.7%
- 379
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.1%
1 1138
 
10.7%
- 379
 
3.6%

hg_product_33
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.5 KiB
0.0
2279 
-1.0
647 
1.0
491 

Length

Max length4
Median length3
Mean length3.1893474
Min length3

Characters and Unicode

Total characters10898
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 647
 
18.9%
1.0 491
 
14.4%

Length

2023-12-31T13:51:11.997446image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:12.132306image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.3%
. 3417
31.4%
1 1138
 
10.4%
- 647
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.7%
Other Punctuation 3417
31.4%
Dash Punctuation 647
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 647
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10898
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.3%
. 3417
31.4%
1 1138
 
10.4%
- 647
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.3%
. 3417
31.4%
1 1138
 
10.4%
- 647
 
5.9%

hg_product_34
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.4 KiB
0.0
2279 
1.0
616 
-1.0
522 

Length

Max length4
Median length3
Mean length3.1527656
Min length3

Characters and Unicode

Total characters10773
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 616
 
18.0%
-1.0 522
 
15.3%

Length

2023-12-31T13:51:12.264662image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:12.396527image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.9%
. 3417
31.7%
1 1138
 
10.6%
- 522
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.4%
Other Punctuation 3417
31.7%
Dash Punctuation 522
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.9%
. 3417
31.7%
1 1138
 
10.6%
- 522
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.9%
. 3417
31.7%
1 1138
 
10.6%
- 522
 
4.8%

hg_product_35
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1110 
1.0
 
28

Length

Max length4
Median length3
Mean length3.3248464
Min length3

Characters and Unicode

Total characters11361
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1110
32.5%
1.0 28
 
0.8%

Length

2023-12-31T13:51:12.528558image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:12.649330image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1110
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

hg_product_36
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.7 KiB
0.0
2279 
-1.0
839 
1.0
299 

Length

Max length4
Median length3
Mean length3.245537
Min length3

Characters and Unicode

Total characters11090
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 839
 
24.6%
1.0 299
 
8.8%

Length

2023-12-31T13:51:12.780777image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:12.969665image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.4%
. 3417
30.8%
1 1138
 
10.3%
- 839
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.6%
Other Punctuation 3417
30.8%
Dash Punctuation 839
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 839
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.4%
. 3417
30.8%
1 1138
 
10.3%
- 839
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.4%
. 3417
30.8%
1 1138
 
10.3%
- 839
 
7.6%

hg_product_37
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
981 
1.0
 
157

Length

Max length4
Median length3
Mean length3.2870939
Min length3

Characters and Unicode

Total characters11232
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 981
28.7%
1.0 157
 
4.6%

Length

2023-12-31T13:51:13.113095image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:13.228947image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 981
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.8%
Other Punctuation 3417
30.4%
Dash Punctuation 981
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 981
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 981
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 981
 
8.7%

hg_product_38
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.7 KiB
0.0
2279 
-1.0
848 
1.0
290 

Length

Max length4
Median length3
Mean length3.2481709
Min length3

Characters and Unicode

Total characters11099
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 848
 
24.8%
1.0 290
 
8.5%

Length

2023-12-31T13:51:13.499046image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:13.635796image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.6%
Other Punctuation 3417
30.8%
Dash Punctuation 848
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 848
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11099
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.3%
. 3417
30.8%
1 1138
 
10.3%
- 848
 
7.6%

hg_product_39
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
890 
1.0
248 

Length

Max length4
Median length3
Mean length3.2604624
Min length3

Characters and Unicode

Total characters11141
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 890
 
26.0%
1.0 248
 
7.3%

Length

2023-12-31T13:51:13.778814image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:14.120126image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.1%
. 3417
30.7%
1 1138
 
10.2%
- 890
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.3%
Other Punctuation 3417
30.7%
Dash Punctuation 890
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 890
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11141
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.1%
. 3417
30.7%
1 1138
 
10.2%
- 890
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.1%
. 3417
30.7%
1 1138
 
10.2%
- 890
 
8.0%

hg_product_40
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1120 
1.0
 
18

Length

Max length4
Median length3
Mean length3.3277729
Min length3

Characters and Unicode

Total characters11371
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1120
32.8%
1.0 18
 
0.5%

Length

2023-12-31T13:51:14.259357image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:14.401719image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1120
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1120
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11371
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1120
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11371
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1120
 
9.8%

hg_product_41
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
951 
1.0
 
187

Length

Max length4
Median length3
Mean length3.2783143
Min length3

Characters and Unicode

Total characters11202
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 951
27.8%
1.0 187
 
5.5%

Length

2023-12-31T13:51:14.538703image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:14.666250image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 951
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.0%
Other Punctuation 3417
30.5%
Dash Punctuation 951
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 951
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 951
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 951
 
8.5%

hg_product_42
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
927 
1.0
 
211

Length

Max length4
Median length3
Mean length3.2712906
Min length3

Characters and Unicode

Total characters11178
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 927
27.1%
1.0 211
 
6.2%

Length

2023-12-31T13:51:14.804405image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:14.933846image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 927
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.1%
Other Punctuation 3417
30.6%
Dash Punctuation 927
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 927
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11178
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 927
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11178
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 927
 
8.3%

hg_product_43
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1101 
1.0
 
37

Length

Max length4
Median length3
Mean length3.3222125
Min length3

Characters and Unicode

Total characters11352
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1101
32.2%
1.0 37
 
1.1%

Length

2023-12-31T13:51:15.068117image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:15.212287image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1101
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1101
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1101
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1101
 
9.7%

hg_product_44
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
944 
1.0
 
194

Length

Max length4
Median length3
Mean length3.2762657
Min length3

Characters and Unicode

Total characters11195
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 944
27.6%
1.0 194
 
5.7%

Length

2023-12-31T13:51:15.362847image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:15.498142image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 944
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.0%
Other Punctuation 3417
30.5%
Dash Punctuation 944
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 944
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 944
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 944
 
8.4%

hg_product_45
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.7 KiB
0.0
2279 
-1.0
758 
1.0
380 

Length

Max length4
Median length3
Mean length3.221832
Min length3

Characters and Unicode

Total characters11009
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 758
 
22.2%
1.0 380
 
11.1%

Length

2023-12-31T13:51:15.642292image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:15.772241image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.7%
. 3417
31.0%
1 1138
 
10.3%
- 758
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.1%
Other Punctuation 3417
31.0%
Dash Punctuation 758
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 758
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.7%
. 3417
31.0%
1 1138
 
10.3%
- 758
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.7%
. 3417
31.0%
1 1138
 
10.3%
- 758
 
6.9%

hg_product_46
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1132 
1.0
 
6

Length

Max length4
Median length3
Mean length3.3312848
Min length3

Characters and Unicode

Total characters11383
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1132
33.1%
1.0 6
 
0.2%

Length

2023-12-31T13:51:15.912425image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:16.057245image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1132
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11383
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

hg_product_47
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.4 KiB
0.0
2279 
1.0
658 
-1.0
480 

Length

Max length4
Median length3
Mean length3.1404741
Min length3

Characters and Unicode

Total characters10731
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 658
 
19.3%
-1.0 480
 
14.0%

Length

2023-12-31T13:51:16.221010image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:16.345040image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.1%
. 3417
31.8%
1 1138
 
10.6%
- 480
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.7%
Other Punctuation 3417
31.8%
Dash Punctuation 480
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 480
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10731
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.1%
. 3417
31.8%
1 1138
 
10.6%
- 480
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.1%
. 3417
31.8%
1 1138
 
10.6%
- 480
 
4.5%

hg_product_48
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.1 KiB
0.0
2279 
1.0
951 
-1.0
 
187

Length

Max length4
Median length3
Mean length3.0547264
Min length3

Characters and Unicode

Total characters10438
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 951
27.8%
-1.0 187
 
5.5%

Length

2023-12-31T13:51:16.481855image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:16.604232image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
54.6%
. 3417
32.7%
1 1138
 
10.9%
- 187
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
65.5%
Other Punctuation 3417
32.7%
Dash Punctuation 187
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10438
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
54.6%
. 3417
32.7%
1 1138
 
10.9%
- 187
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
54.6%
. 3417
32.7%
1 1138
 
10.9%
- 187
 
1.8%

hg_product_49
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1012 
1.0
 
126

Length

Max length4
Median length3
Mean length3.2961662
Min length3

Characters and Unicode

Total characters11263
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1012
29.6%
1.0 126
 
3.7%

Length

2023-12-31T13:51:16.734926image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:16.855904image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1012
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.7%
Other Punctuation 3417
30.3%
Dash Punctuation 1012
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1012
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11263
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1012
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1012
 
9.0%

hg_product_50
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
665 
1.0
473 

Length

Max length4
Median length3
Mean length3.1946152
Min length3

Characters and Unicode

Total characters10916
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 665
 
19.5%
1.0 473
 
13.8%

Length

2023-12-31T13:51:16.998766image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:17.123352image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 665
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.6%
Other Punctuation 3417
31.3%
Dash Punctuation 665
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10916
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 665
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10916
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 665
 
6.1%

hg_product_51
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
987 
1.0
 
151

Length

Max length4
Median length3
Mean length3.2888499
Min length3

Characters and Unicode

Total characters11238
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 987
28.9%
1.0 151
 
4.4%

Length

2023-12-31T13:51:17.260488image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:17.380473image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 987
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.8%
Other Punctuation 3417
30.4%
Dash Punctuation 987
 
8.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 987
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 987
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 987
 
8.8%

hg_product_52
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1064 
1.0
 
74

Length

Max length4
Median length3
Mean length3.3113843
Min length3

Characters and Unicode

Total characters11315
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1064
31.1%
1.0 74
 
2.2%

Length

2023-12-31T13:51:17.506847image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:17.623989image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1064
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1064
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1064
 
9.4%

hg_product_53
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1094 
1.0
 
44

Length

Max length4
Median length3
Mean length3.3201639
Min length3

Characters and Unicode

Total characters11345
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1094
32.0%
1.0 44
 
1.3%

Length

2023-12-31T13:51:17.750592image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:17.869496image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1094
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1094
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11345
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1094
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11345
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1094
 
9.6%

hg_product_54
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1128 
1.0
 
10

Length

Max length4
Median length3
Mean length3.3301141
Min length3

Characters and Unicode

Total characters11379
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1128
33.0%
1.0 10
 
0.3%

Length

2023-12-31T13:51:17.995238image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:18.113938image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1128
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

hg_product_55
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.5 KiB
0.0
2279 
-1.0
603 
1.0
535 

Length

Max length4
Median length3
Mean length3.1764706
Min length3

Characters and Unicode

Total characters10854
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 603
 
17.6%
1.0 535
 
15.7%

Length

2023-12-31T13:51:18.233002image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:18.341668image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 603
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.0%
Other Punctuation 3417
31.5%
Dash Punctuation 603
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 603
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10854
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 603
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.5%
. 3417
31.5%
1 1138
 
10.5%
- 603
 
5.6%

hg_product_56
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1133 
1.0
 
5

Length

Max length4
Median length3
Mean length3.3315774
Min length3

Characters and Unicode

Total characters11384
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1133
33.2%
1.0 5
 
0.1%

Length

2023-12-31T13:51:18.490939image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:18.614192image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1133
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1133
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1133
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1133
 
10.0%

hg_product_57
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
870 
1.0
268 

Length

Max length4
Median length3
Mean length3.2546093
Min length3

Characters and Unicode

Total characters11121
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 870
 
25.5%
1.0 268
 
7.8%

Length

2023-12-31T13:51:18.742362image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:18.865564image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 870
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.5%
Other Punctuation 3417
30.7%
Dash Punctuation 870
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 870
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 870
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 870
 
7.8%

hg_product_58
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1134 
1.0
 
4

Length

Max length4
Median length3
Mean length3.3318701
Min length3

Characters and Unicode

Total characters11385
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1134
33.2%
1.0 4
 
0.1%

Length

2023-12-31T13:51:18.993468image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:19.122081image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1134
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1134
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11385
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1134
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1134
 
10.0%

hg_product_59
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:19.250616image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:19.361324image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_60
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1123 
1.0
 
15

Length

Max length4
Median length3
Mean length3.3286509
Min length3

Characters and Unicode

Total characters11374
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1123
32.9%
1.0 15
 
0.4%

Length

2023-12-31T13:51:19.494280image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:19.634561image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1123
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1123
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1123
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1123
 
9.9%

hg_product_61
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1137 
1.0
 
1

Length

Max length4
Median length3
Mean length3.332748
Min length3

Characters and Unicode

Total characters11388
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1137
33.3%
1.0 1
 
< 0.1%

Length

2023-12-31T13:51:19.771551image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:19.882108image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1137
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

hg_product_62
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1015 
1.0
 
123

Length

Max length4
Median length3
Mean length3.2970442
Min length3

Characters and Unicode

Total characters11266
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1015
29.7%
1.0 123
 
3.6%

Length

2023-12-31T13:51:20.014526image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:20.135098image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1015
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.7%
Other Punctuation 3417
30.3%
Dash Punctuation 1015
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1015
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11266
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1015
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.3%
1 1138
 
10.1%
- 1015
 
9.0%

hg_product_63
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
871 
1.0
267 

Length

Max length4
Median length3
Mean length3.254902
Min length3

Characters and Unicode

Total characters11122
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 871
 
25.5%
1.0 267
 
7.8%

Length

2023-12-31T13:51:20.269643image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:20.390561image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 871
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.4%
Other Punctuation 3417
30.7%
Dash Punctuation 871
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 871
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11122
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 871
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 871
 
7.8%

hg_product_64
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1131 
1.0
 
7

Length

Max length4
Median length3
Mean length3.3309921
Min length3

Characters and Unicode

Total characters11382
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1131
33.1%
1.0 7
 
0.2%

Length

2023-12-31T13:51:20.521497image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:20.638044image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1131
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11382
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

hg_product_65
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1029 
1.0
 
109

Length

Max length4
Median length3
Mean length3.3011414
Min length3

Characters and Unicode

Total characters11280
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1029
30.1%
1.0 109
 
3.2%

Length

2023-12-31T13:51:20.767850image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:20.880176image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1029
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1029
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1029
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1029
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1029
 
9.1%

hg_product_66
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1044 
1.0
 
94

Length

Max length4
Median length3
Mean length3.3055312
Min length3

Characters and Unicode

Total characters11295
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1044
30.6%
1.0 94
 
2.8%

Length

2023-12-31T13:51:21.005474image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:21.119953image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1044
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.5%
Other Punctuation 3417
30.3%
Dash Punctuation 1044
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11295
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1044
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1044
 
9.2%

hg_product_67
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.1 KiB
0.0
2279 
1.0
896 
-1.0
242 

Length

Max length4
Median length3
Mean length3.0708224
Min length3

Characters and Unicode

Total characters10493
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 896
 
26.2%
-1.0 242
 
7.1%

Length

2023-12-31T13:51:21.251388image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:21.366800image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
54.3%
. 3417
32.6%
1 1138
 
10.8%
- 242
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
65.1%
Other Punctuation 3417
32.6%
Dash Punctuation 242
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
54.3%
. 3417
32.6%
1 1138
 
10.8%
- 242
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
54.3%
. 3417
32.6%
1 1138
 
10.8%
- 242
 
2.3%

hg_product_68
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
975 
1.0
 
163

Length

Max length4
Median length3
Mean length3.285338
Min length3

Characters and Unicode

Total characters11226
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 975
28.5%
1.0 163
 
4.8%

Length

2023-12-31T13:51:21.486652image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:21.591869image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 975
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.9%
Other Punctuation 3417
30.4%
Dash Punctuation 975
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 975
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11226
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 975
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 975
 
8.7%

hg_product_69
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
679 
1.0
459 

Length

Max length4
Median length3
Mean length3.1987123
Min length3

Characters and Unicode

Total characters10930
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 679
 
19.9%
1.0 459
 
13.4%

Length

2023-12-31T13:51:21.711067image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:21.834984image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.1%
. 3417
31.3%
1 1138
 
10.4%
- 679
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.5%
Other Punctuation 3417
31.3%
Dash Punctuation 679
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 679
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.1%
. 3417
31.3%
1 1138
 
10.4%
- 679
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.1%
. 3417
31.3%
1 1138
 
10.4%
- 679
 
6.2%

hg_product_70
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1023 
1.0
 
115

Length

Max length4
Median length3
Mean length3.2993854
Min length3

Characters and Unicode

Total characters11274
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1023
29.9%
1.0 115
 
3.4%

Length

2023-12-31T13:51:21.966075image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:22.086238image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1023
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1023
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1023
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1023
 
9.1%

hg_product_71
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1097 
1.0
 
41

Length

Max length4
Median length3
Mean length3.3210418
Min length3

Characters and Unicode

Total characters11348
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1097
32.1%
1.0 41
 
1.2%

Length

2023-12-31T13:51:22.205108image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:22.312110image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1097
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1097
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1097
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1097
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1097
 
9.7%

hg_product_72
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
908 
1.0
230 

Length

Max length4
Median length3
Mean length3.2657302
Min length3

Characters and Unicode

Total characters11159
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 908
 
26.6%
1.0 230
 
6.7%

Length

2023-12-31T13:51:22.432868image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:22.538087image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 908
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.2%
Other Punctuation 3417
30.6%
Dash Punctuation 908
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 908
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11159
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 908
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 908
 
8.1%

hg_product_73
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
770 
-1.0
368 

Length

Max length4
Median length3
Mean length3.1076968
Min length3

Characters and Unicode

Total characters10619
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 770
 
22.5%
-1.0 368
 
10.8%

Length

2023-12-31T13:51:22.664893image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:22.782206image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.2%
1 1138
 
10.7%
- 368
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
64.4%
Other Punctuation 3417
32.2%
Dash Punctuation 368
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10619
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.2%
1 1138
 
10.7%
- 368
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10619
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.6%
. 3417
32.2%
1 1138
 
10.7%
- 368
 
3.5%

hg_product_74
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1088 
1.0
 
50

Length

Max length4
Median length3
Mean length3.318408
Min length3

Characters and Unicode

Total characters11339
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1088
31.8%
1.0 50
 
1.5%

Length

2023-12-31T13:51:22.907043image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:23.021104image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.1%
Dash Punctuation 1088
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1088
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

hg_product_75
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1031 
1.0
 
107

Length

Max length4
Median length3
Mean length3.3017267
Min length3

Characters and Unicode

Total characters11282
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1031
30.2%
1.0 107
 
3.1%

Length

2023-12-31T13:51:23.144879image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:23.265981image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1031
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1031
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1031
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1031
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1031
 
9.1%

hg_product_76
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
955 
1.0
 
183

Length

Max length4
Median length3
Mean length3.2794849
Min length3

Characters and Unicode

Total characters11206
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 955
27.9%
1.0 183
 
5.4%

Length

2023-12-31T13:51:23.387170image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:23.507017image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 955
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.0%
Other Punctuation 3417
30.5%
Dash Punctuation 955
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 955
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11206
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 955
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.2%
- 955
 
8.5%

hg_product_77
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
925 
1.0
 
213

Length

Max length4
Median length3
Mean length3.2707053
Min length3

Characters and Unicode

Total characters11176
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 925
27.1%
1.0 213
 
6.2%

Length

2023-12-31T13:51:23.641115image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:23.758360image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 925
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.1%
Other Punctuation 3417
30.6%
Dash Punctuation 925
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 925
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 925
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.0%
. 3417
30.6%
1 1138
 
10.2%
- 925
 
8.3%

hg_product_78
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1059 
1.0
 
79

Length

Max length4
Median length3
Mean length3.309921
Min length3

Characters and Unicode

Total characters11310
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1059
31.0%
1.0 79
 
2.3%

Length

2023-12-31T13:51:23.880518image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:23.988603image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1059
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1059
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1059
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1059
 
9.4%

hg_product_79
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
989 
1.0
 
149

Length

Max length4
Median length3
Mean length3.2894352
Min length3

Characters and Unicode

Total characters11240
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 989
28.9%
1.0 149
 
4.4%

Length

2023-12-31T13:51:24.106677image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:24.215765image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 989
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.8%
Other Punctuation 3417
30.4%
Dash Punctuation 989
 
8.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 989
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 989
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.7%
. 3417
30.4%
1 1138
 
10.1%
- 989
 
8.8%

hg_product_80
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1063 
1.0
 
75

Length

Max length4
Median length3
Mean length3.3110916
Min length3

Characters and Unicode

Total characters11314
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1063
31.1%
1.0 75
 
2.2%

Length

2023-12-31T13:51:24.331370image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:24.662122image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1063
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1063
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1063
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1063
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1063
 
9.4%

hg_product_81
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1004 
1.0
 
134

Length

Max length4
Median length3
Mean length3.293825
Min length3

Characters and Unicode

Total characters11255
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1004
29.4%
1.0 134
 
3.9%

Length

2023-12-31T13:51:24.797682image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:24.919320image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1004
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.7%
Other Punctuation 3417
30.4%
Dash Punctuation 1004
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1004
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11255
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1004
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1004
 
8.9%

hg_product_82
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:25.045709image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:25.155352image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_83
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.4 KiB
0.0
2279 
1.0
610 
-1.0
528 

Length

Max length4
Median length3
Mean length3.1545215
Min length3

Characters and Unicode

Total characters10779
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 610
 
17.9%
-1.0 528
 
15.5%

Length

2023-12-31T13:51:25.271816image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:25.387248image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.8%
. 3417
31.7%
1 1138
 
10.6%
- 528
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.4%
Other Punctuation 3417
31.7%
Dash Punctuation 528
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 528
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10779
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.8%
. 3417
31.7%
1 1138
 
10.6%
- 528
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10779
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.8%
. 3417
31.7%
1 1138
 
10.6%
- 528
 
4.9%

hg_product_84
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1084 
1.0
 
54

Length

Max length4
Median length3
Mean length3.3172373
Min length3

Characters and Unicode

Total characters11335
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1084
31.7%
1.0 54
 
1.6%

Length

2023-12-31T13:51:25.520151image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:25.638132image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.1%
1 1138
 
10.0%
- 1084
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.1%
Dash Punctuation 1084
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1084
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11335
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.1%
1 1138
 
10.0%
- 1084
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11335
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.1%
1 1138
 
10.0%
- 1084
 
9.6%

hg_product_85
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:25.770173image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:25.880866image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_86
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1103 
1.0
 
35

Length

Max length4
Median length3
Mean length3.3227978
Min length3

Characters and Unicode

Total characters11354
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1103
32.3%
1.0 35
 
1.0%

Length

2023-12-31T13:51:26.003853image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:26.118597image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1103
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1103
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1103
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1103
 
9.7%

hg_product_87
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
745 
-1.0
393 

Length

Max length4
Median length3
Mean length3.1150132
Min length3

Characters and Unicode

Total characters10644
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 745
 
21.8%
-1.0 393
 
11.5%

Length

2023-12-31T13:51:26.243586image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:26.365701image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
64.2%
Other Punctuation 3417
32.1%
Dash Punctuation 393
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

hg_product_88
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
716 
1.0
422 

Length

Max length4
Median length3
Mean length3.2095405
Min length3

Characters and Unicode

Total characters10967
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 716
 
21.0%
1.0 422
 
12.4%

Length

2023-12-31T13:51:26.489318image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:26.610126image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.2%
1 1138
 
10.4%
- 716
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.3%
Other Punctuation 3417
31.2%
Dash Punctuation 716
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 716
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10967
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.2%
1 1138
 
10.4%
- 716
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.2%
1 1138
 
10.4%
- 716
 
6.5%

hg_product_89
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1035 
1.0
 
103

Length

Max length4
Median length3
Mean length3.3028973
Min length3

Characters and Unicode

Total characters11286
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1035
30.3%
1.0 103
 
3.0%

Length

2023-12-31T13:51:26.738238image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:26.853299image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1035
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1035
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1035
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1035
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1035
 
9.2%

hg_product_90
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1003 
1.0
 
135

Length

Max length4
Median length3
Mean length3.2935323
Min length3

Characters and Unicode

Total characters11254
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1003
29.4%
1.0 135
 
4.0%

Length

2023-12-31T13:51:26.978990image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:27.094450image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1003
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.7%
Other Punctuation 3417
30.4%
Dash Punctuation 1003
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1003
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11254
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1003
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1003
 
8.9%

hg_product_91
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1137 
1.0
 
1

Length

Max length4
Median length3
Mean length3.332748
Min length3

Characters and Unicode

Total characters11388
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1137
33.3%
1.0 1
 
< 0.1%

Length

2023-12-31T13:51:27.215785image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:27.326234image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1137
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

hg_product_92
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1119 
1.0
 
19

Length

Max length4
Median length3
Mean length3.3274802
Min length3

Characters and Unicode

Total characters11370
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1119
32.7%
1.0 19
 
0.6%

Length

2023-12-31T13:51:27.444383image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:27.554721image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1119
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1119
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1119
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1119
 
9.8%

hg_product_93
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:27.677536image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:27.787995image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_94
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:27.907272image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:28.018899image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_95
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1068 
1.0
 
70

Length

Max length4
Median length3
Mean length3.3125549
Min length3

Characters and Unicode

Total characters11319
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1068
31.3%
1.0 70
 
2.0%

Length

2023-12-31T13:51:28.144624image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:28.256067image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1068
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1068
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1068
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11319
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1068
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1068
 
9.4%

hg_product_96
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
965 
1.0
 
173

Length

Max length4
Median length3
Mean length3.2824115
Min length3

Characters and Unicode

Total characters11216
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 965
28.2%
1.0 173
 
5.1%

Length

2023-12-31T13:51:28.378001image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:28.493916image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.1%
- 965
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.9%
Other Punctuation 3417
30.5%
Dash Punctuation 965
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 965
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.1%
- 965
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.8%
. 3417
30.5%
1 1138
 
10.1%
- 965
 
8.6%

hg_product_97
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1122 
1.0
 
16

Length

Max length4
Median length3
Mean length3.3283582
Min length3

Characters and Unicode

Total characters11373
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1122
32.8%
1.0 16
 
0.5%

Length

2023-12-31T13:51:28.614601image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:28.731363image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1122
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1122
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1122
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1122
 
9.9%

hg_product_98
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1114 
1.0
 
24

Length

Max length4
Median length3
Mean length3.326017
Min length3

Characters and Unicode

Total characters11365
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1114
32.6%
1.0 24
 
0.7%

Length

2023-12-31T13:51:28.855319image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:28.972091image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1114
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1114
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1114
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1114
 
9.8%

hg_product_99
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1110 
1.0
 
28

Length

Max length4
Median length3
Mean length3.3248464
Min length3

Characters and Unicode

Total characters11361
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1110
32.5%
1.0 28
 
0.8%

Length

2023-12-31T13:51:29.136717image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:29.288222image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1110
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1110
 
9.8%

hg_product_100
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1098 
1.0
 
40

Length

Max length4
Median length3
Mean length3.3213345
Min length3

Characters and Unicode

Total characters11349
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1098
32.1%
1.0 40
 
1.2%

Length

2023-12-31T13:51:29.480963image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:29.614127image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1098
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1098
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1098
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1098
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1098
 
9.7%

hg_product_101
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1088 
1.0
 
50

Length

Max length4
Median length3
Mean length3.318408
Min length3

Characters and Unicode

Total characters11339
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1088
31.8%
1.0 50
 
1.5%

Length

2023-12-31T13:51:29.761106image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:29.917005image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.1%
Dash Punctuation 1088
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1088
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1088
 
9.6%

hg_product_102
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
711 
1.0
427 

Length

Max length4
Median length3
Mean length3.2080773
Min length3

Characters and Unicode

Total characters10962
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 711
 
20.8%
1.0 427
 
12.5%

Length

2023-12-31T13:51:30.058150image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:30.213350image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 711
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.3%
Other Punctuation 3417
31.2%
Dash Punctuation 711
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 711
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 711
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 711
 
6.5%

hg_product_103
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1005 
1.0
 
133

Length

Max length4
Median length3
Mean length3.2941176
Min length3

Characters and Unicode

Total characters11256
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1005
29.4%
1.0 133
 
3.9%

Length

2023-12-31T13:51:30.371069image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:30.520353image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1005
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.7%
Other Punctuation 3417
30.4%
Dash Punctuation 1005
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1005
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1005
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.6%
. 3417
30.4%
1 1138
 
10.1%
- 1005
 
8.9%

hg_product_104
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1115 
1.0
 
23

Length

Max length4
Median length3
Mean length3.3263096
Min length3

Characters and Unicode

Total characters11366
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1115
32.6%
1.0 23
 
0.7%

Length

2023-12-31T13:51:30.681623image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:30.816960image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1115
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1115
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11366
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1115
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1115
 
9.8%

hg_product_105
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1018 
1.0
 
120

Length

Max length4
Median length3
Mean length3.2979222
Min length3

Characters and Unicode

Total characters11269
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1018
29.8%
1.0 120
 
3.5%

Length

2023-12-31T13:51:30.967025image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:31.099681image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1018
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1018
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1018
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1018
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1018
 
9.0%

hg_product_106
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1127 
1.0
 
11

Length

Max length4
Median length3
Mean length3.3298215
Min length3

Characters and Unicode

Total characters11378
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1127
33.0%
1.0 11
 
0.3%

Length

2023-12-31T13:51:31.234197image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:31.355843image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1127
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1127
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1127
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1127
 
9.9%

hg_product_107
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1126 
1.0
 
12

Length

Max length4
Median length3
Mean length3.3295288
Min length3

Characters and Unicode

Total characters11377
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1126
33.0%
1.0 12
 
0.4%

Length

2023-12-31T13:51:31.485697image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:31.610877image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1126
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

hg_product_108
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:31.743146image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:31.861668image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_109
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1137 
1.0
 
1

Length

Max length4
Median length3
Mean length3.332748
Min length3

Characters and Unicode

Total characters11388
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1137
33.3%
1.0 1
 
< 0.1%

Length

2023-12-31T13:51:31.989047image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:32.108522image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1137
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

hg_product_110
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1130 
1.0
 
8

Length

Max length4
Median length3
Mean length3.3306994
Min length3

Characters and Unicode

Total characters11381
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1130
33.1%
1.0 8
 
0.2%

Length

2023-12-31T13:51:32.232151image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:32.352836image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1130
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1130
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1130
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1130
 
9.9%

hg_product_111
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:32.488373image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:32.605616image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_112
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1040 
1.0
 
98

Length

Max length4
Median length3
Mean length3.3043606
Min length3

Characters and Unicode

Total characters11291
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1040
30.4%
1.0 98
 
2.9%

Length

2023-12-31T13:51:32.736517image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:32.870945image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1040
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.5%
Other Punctuation 3417
30.3%
Dash Punctuation 1040
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1040
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1040
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1040
 
9.2%

hg_product_113
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:33.023948image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:33.157879image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_114
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1045 
1.0
 
93

Length

Max length4
Median length3
Mean length3.3058238
Min length3

Characters and Unicode

Total characters11296
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1045
30.6%
1.0 93
 
2.7%

Length

2023-12-31T13:51:33.295826image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:33.434570image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1045
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.5%
Other Punctuation 3417
30.2%
Dash Punctuation 1045
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1045
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1045
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.2%
1 1138
 
10.1%
- 1045
 
9.3%

hg_product_115
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1132 
1.0
 
6

Length

Max length4
Median length3
Mean length3.3312848
Min length3

Characters and Unicode

Total characters11383
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1132
33.1%
1.0 6
 
0.2%

Length

2023-12-31T13:51:33.572493image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:33.697383image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1132
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11383
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1132
 
9.9%

hg_product_116
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1117 
1.0
 
21

Length

Max length4
Median length3
Mean length3.3268949
Min length3

Characters and Unicode

Total characters11368
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1117
32.7%
1.0 21
 
0.6%

Length

2023-12-31T13:51:33.830847image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:33.952466image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1117
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1117
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11368
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1117
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1117
 
9.8%

hg_product_117
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1126 
1.0
 
12

Length

Max length4
Median length3
Mean length3.3295288
Min length3

Characters and Unicode

Total characters11377
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1126
33.0%
1.0 12
 
0.4%

Length

2023-12-31T13:51:34.087932image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:34.229167image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1126
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

hg_product_118
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1137 
1.0
 
1

Length

Max length4
Median length3
Mean length3.332748
Min length3

Characters and Unicode

Total characters11388
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1137
33.3%
1.0 1
 
< 0.1%

Length

2023-12-31T13:51:34.376613image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:34.518045image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1137
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

hg_product_119
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1020 
1.0
 
118

Length

Max length4
Median length3
Mean length3.2985075
Min length3

Characters and Unicode

Total characters11271
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1020
29.9%
1.0 118
 
3.5%

Length

2023-12-31T13:51:34.657743image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:34.808646image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1020
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.6%
Other Punctuation 3417
30.3%
Dash Punctuation 1020
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1020
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1020
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.5%
. 3417
30.3%
1 1138
 
10.1%
- 1020
 
9.0%

hg_product_120
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1113 
1.0
 
25

Length

Max length4
Median length3
Mean length3.3257243
Min length3

Characters and Unicode

Total characters11364
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1113
32.6%
1.0 25
 
0.7%

Length

2023-12-31T13:51:34.973716image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:35.114753image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1113
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1113
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1113
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1113
 
9.8%

hg_product_121
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1135 
1.0
 
3

Length

Max length4
Median length3
Mean length3.3321627
Min length3

Characters and Unicode

Total characters11386
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1135
33.2%
1.0 3
 
0.1%

Length

2023-12-31T13:51:35.277801image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:35.440628image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1135
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1135
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11386
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1135
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1135
 
10.0%

hg_product_122
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1138 

Length

Max length4
Median length3
Mean length3.3330407
Min length3

Characters and Unicode

Total characters11389
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1138
33.3%

Length

2023-12-31T13:51:35.592650image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:35.940912image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1138
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
- 1138
 
10.0%
1 1138
 
10.0%

hg_product_123
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.9 KiB
0.0
2279 
-1.0
1041 
1.0
 
97

Length

Max length4
Median length3
Mean length3.3046532
Min length3

Characters and Unicode

Total characters11292
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1041
30.5%
1.0 97
 
2.8%

Length

2023-12-31T13:51:36.069159image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:36.191812image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1041
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.5%
Other Punctuation 3417
30.3%
Dash Punctuation 1041
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1041
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1041
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.4%
. 3417
30.3%
1 1138
 
10.1%
- 1041
 
9.2%

hg_product_124
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
734 
1.0
404 

Length

Max length4
Median length3
Mean length3.2148083
Min length3

Characters and Unicode

Total characters10985
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 734
 
21.5%
1.0 404
 
11.8%

Length

2023-12-31T13:51:36.332167image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:36.453548image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.1%
1 1138
 
10.4%
- 734
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.2%
Other Punctuation 3417
31.1%
Dash Punctuation 734
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 734
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10985
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.1%
1 1138
 
10.4%
- 734
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10985
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.9%
. 3417
31.1%
1 1138
 
10.4%
- 734
 
6.7%

hg_product_125
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
737 
-1.0
401 

Length

Max length4
Median length3
Mean length3.1173544
Min length3

Characters and Unicode

Total characters10652
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 737
 
21.6%
-1.0 401
 
11.7%

Length

2023-12-31T13:51:36.584859image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:36.708515image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 401
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
64.2%
Other Punctuation 3417
32.1%
Dash Punctuation 401
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 401
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 401
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 401
 
3.8%

hg_product_126
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1092 
1.0
 
46

Length

Max length4
Median length3
Mean length3.3195786
Min length3

Characters and Unicode

Total characters11343
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1092
32.0%
1.0 46
 
1.3%

Length

2023-12-31T13:51:36.836984image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:36.953368image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1092
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1092
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1092
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11343
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1092
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1092
 
9.6%

hg_product_127
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1099 
1.0
 
39

Length

Max length4
Median length3
Mean length3.3216272
Min length3

Characters and Unicode

Total characters11350
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1099
32.2%
1.0 39
 
1.1%

Length

2023-12-31T13:51:37.081055image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:37.228940image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1099
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1099
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

hg_product_128
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:37.451195image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:37.592918image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_129
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.1 KiB
0.0
2279 
1.0
909 
-1.0
229 

Length

Max length4
Median length3
Mean length3.0670179
Min length3

Characters and Unicode

Total characters10480
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 909
 
26.6%
-1.0 229
 
6.7%

Length

2023-12-31T13:51:37.731278image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:37.860108image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
54.4%
. 3417
32.6%
1 1138
 
10.9%
- 229
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
65.2%
Other Punctuation 3417
32.6%
Dash Punctuation 229
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 229
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
54.4%
. 3417
32.6%
1 1138
 
10.9%
- 229
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
54.4%
. 3417
32.6%
1 1138
 
10.9%
- 229
 
2.2%

hg_product_130
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1129 
1.0
 
9

Length

Max length4
Median length3
Mean length3.3304068
Min length3

Characters and Unicode

Total characters11380
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1129
33.0%
1.0 9
 
0.3%

Length

2023-12-31T13:51:37.991228image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:38.114254image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1129
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1129
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1129
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1129
 
9.9%

hg_product_131
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1126 
1.0
 
12

Length

Max length4
Median length3
Mean length3.3295288
Min length3

Characters and Unicode

Total characters11377
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1126
33.0%
1.0 12
 
0.4%

Length

2023-12-31T13:51:38.244919image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:38.368356image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1126
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1126
 
9.9%

hg_product_132
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
942 
1.0
 
196

Length

Max length4
Median length3
Mean length3.2756804
Min length3

Characters and Unicode

Total characters11193
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 942
27.6%
1.0 196
 
5.7%

Length

2023-12-31T13:51:38.523367image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:38.649067image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 942
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.1%
Other Punctuation 3417
30.5%
Dash Punctuation 942
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 942
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.9%
. 3417
30.5%
1 1138
 
10.2%
- 942
 
8.4%

hg_product_133
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1128 
1.0
 
10

Length

Max length4
Median length3
Mean length3.3301141
Min length3

Characters and Unicode

Total characters11379
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1128
33.0%
1.0 10
 
0.3%

Length

2023-12-31T13:51:38.784790image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:38.912442image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1128
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

hg_product_134
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1128 
1.0
 
10

Length

Max length4
Median length3
Mean length3.3301141
Min length3

Characters and Unicode

Total characters11379
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1128
33.0%
1.0 10
 
0.3%

Length

2023-12-31T13:51:39.069249image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:39.220206image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.0%
Dash Punctuation 1128
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.0%
1 1138
 
10.0%
- 1128
 
9.9%

hg_product_135
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1137 
1.0
 
1

Length

Max length4
Median length3
Mean length3.332748
Min length3

Characters and Unicode

Total characters11388
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1137
33.3%
1.0 1
 
< 0.1%

Length

2023-12-31T13:51:39.384177image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:39.536285image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1137
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1137
 
10.0%

hg_product_136
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1136 
1.0
 
2

Length

Max length4
Median length3
Mean length3.3324554
Min length3

Characters and Unicode

Total characters11387
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1136
33.2%
1.0 2
 
0.1%

Length

2023-12-31T13:51:39.699618image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:39.852279image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1136
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1136
 
10.0%

hg_product_137
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1105 
1.0
 
33

Length

Max length4
Median length3
Mean length3.3233831
Min length3

Characters and Unicode

Total characters11356
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1105
32.3%
1.0 33
 
1.0%

Length

2023-12-31T13:51:39.992233image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:40.127045image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1105
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1105
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11356
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1105
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11356
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1105
 
9.7%

hg_product_138
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1118 
1.0
 
20

Length

Max length4
Median length3
Mean length3.3271876
Min length3

Characters and Unicode

Total characters11369
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1118
32.7%
1.0 20
 
0.6%

Length

2023-12-31T13:51:40.259533image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:40.378159image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1118
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.1%
Other Punctuation 3417
30.1%
Dash Punctuation 1118
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1118
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.1%
. 3417
30.1%
1 1138
 
10.0%
- 1118
 
9.8%

hg_product_139
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
698 
1.0
440 

Length

Max length4
Median length3
Mean length3.2042728
Min length3

Characters and Unicode

Total characters10949
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 698
 
20.4%
1.0 440
 
12.9%

Length

2023-12-31T13:51:40.504558image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:40.748004image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 698
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.4%
Other Punctuation 3417
31.2%
Dash Punctuation 698
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 698
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 698
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.0%
. 3417
31.2%
1 1138
 
10.4%
- 698
 
6.4%

hg_product_140
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
697 
-1.0
441 

Length

Max length4
Median length3
Mean length3.1290606
Min length3

Characters and Unicode

Total characters10692
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 697
 
20.4%
-1.0 441
 
12.9%

Length

2023-12-31T13:51:40.898970image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:41.028748image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.3%
. 3417
32.0%
1 1138
 
10.6%
- 441
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
63.9%
Other Punctuation 3417
32.0%
Dash Punctuation 441
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 441
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.3%
. 3417
32.0%
1 1138
 
10.6%
- 441
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.3%
. 3417
32.0%
1 1138
 
10.6%
- 441
 
4.1%

hg_product_141
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1078 
1.0
 
60

Length

Max length4
Median length3
Mean length3.3154814
Min length3

Characters and Unicode

Total characters11329
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1078
31.5%
1.0 60
 
1.8%

Length

2023-12-31T13:51:41.170954image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:41.293960image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1078
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.2%
Dash Punctuation 1078
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1078
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1078
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.0%
- 1078
 
9.5%

hg_product_142
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1072 
1.0
 
66

Length

Max length4
Median length3
Mean length3.3137255
Min length3

Characters and Unicode

Total characters11323
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1072
31.4%
1.0 66
 
1.9%

Length

2023-12-31T13:51:41.423042image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:41.545826image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1072
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.4%
Other Punctuation 3417
30.2%
Dash Punctuation 1072
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1072
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1072
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.3%
. 3417
30.2%
1 1138
 
10.1%
- 1072
 
9.5%

hg_product_143
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.8 KiB
0.0
2279 
-1.0
884 
1.0
254 

Length

Max length4
Median length3
Mean length3.2587065
Min length3

Characters and Unicode

Total characters11135
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 884
 
25.9%
1.0 254
 
7.4%

Length

2023-12-31T13:51:41.712740image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:41.832260image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 884
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
61.4%
Other Punctuation 3417
30.7%
Dash Punctuation 884
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 884
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 884
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
51.2%
. 3417
30.7%
1 1138
 
10.2%
- 884
 
7.9%

hg_product_144
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
0.0
2279 
1.0
745 
-1.0
393 

Length

Max length4
Median length3
Mean length3.1150132
Min length3

Characters and Unicode

Total characters10644
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
1.0 745
 
21.8%
-1.0 393
 
11.5%

Length

2023-12-31T13:51:41.965749image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:42.089388image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
64.2%
Other Punctuation 3417
32.1%
Dash Punctuation 393
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
53.5%
. 3417
32.1%
1 1138
 
10.7%
- 393
 
3.7%

hg_product_145
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.6 KiB
0.0
2279 
-1.0
661 
1.0
477 

Length

Max length4
Median length3
Mean length3.1934445
Min length3

Characters and Unicode

Total characters10912
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 661
 
19.3%
1.0 477
 
14.0%

Length

2023-12-31T13:51:42.224803image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:42.344353image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 661
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
62.6%
Other Punctuation 3417
31.3%
Dash Punctuation 661
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 661
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 661
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
52.2%
. 3417
31.3%
1 1138
 
10.4%
- 661
 
6.1%

hg_product_146
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1099 
1.0
 
39

Length

Max length4
Median length3
Mean length3.3216272
Min length3

Characters and Unicode

Total characters11350
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1099
32.2%
1.0 39
 
1.1%

Length

2023-12-31T13:51:42.474854image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:42.595414image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.2%
Other Punctuation 3417
30.1%
Dash Punctuation 1099
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1099
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1099
 
9.7%

hg_product_147
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1089 
1.0
 
49

Length

Max length4
Median length3
Mean length3.3187006
Min length3

Characters and Unicode

Total characters11340
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1089
31.9%
1.0 49
 
1.4%

Length

2023-12-31T13:51:42.723772image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:42.842436image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1089
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.3%
Other Punctuation 3417
30.1%
Dash Punctuation 1089
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1089
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1089
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.2%
. 3417
30.1%
1 1138
 
10.0%
- 1089
 
9.6%

hg_product_148
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size228.0 KiB
0.0
2279 
-1.0
1131 
1.0
 
7

Length

Max length4
Median length3
Mean length3.3309921
Min length3

Characters and Unicode

Total characters11382
Distinct characters4
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 2279
66.7%
-1.0 1131
33.1%
1.0 7
 
0.2%

Length

2023-12-31T13:51:42.970387image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-31T13:51:43.089635image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2279
66.7%
1.0 1138
33.3%

Most occurring characters

ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6834
60.0%
Other Punctuation 3417
30.0%
Dash Punctuation 1131
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5696
83.3%
1 1138
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11382
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5696
50.0%
. 3417
30.0%
1 1138
 
10.0%
- 1131
 
9.9%

country_top
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size224.7 KiB
US
2307 
Other
368 
GB
266 
CA
 
119
AU
 
108
Other values (6)
249 

Length

Max length7
Median length2
Mean length2.3304068
Min length2

Characters and Unicode

Total characters7963
Distinct characters23
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOther
2nd rowFR
3rd rowUS
4th rowUS
5th rowDE

Common Values

ValueCountFrequency (%)
US 2307
67.5%
Other 368
 
10.8%
GB 266
 
7.8%
CA 119
 
3.5%
AU 108
 
3.2%
DE 87
 
2.5%
FR 64
 
1.9%
NL 50
 
1.5%
IN 23
 
0.7%
BR 20
 
0.6%

Length

2023-12-31T13:51:43.222066image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
us 2307
67.5%
other 368
 
10.8%
gb 266
 
7.8%
ca 119
 
3.5%
au 108
 
3.2%
de 87
 
2.5%
fr 64
 
1.9%
nl 50
 
1.5%
in 23
 
0.7%
br 20
 
0.6%

Most occurring characters

ValueCountFrequency (%)
U 2415
30.3%
S 2307
29.0%
O 368
 
4.6%
t 368
 
4.6%
h 368
 
4.6%
e 368
 
4.6%
r 368
 
4.6%
B 286
 
3.6%
G 266
 
3.3%
A 227
 
2.9%
Other values (13) 622
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6461
81.1%
Lowercase Letter 1502
 
18.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 2415
37.4%
S 2307
35.7%
O 368
 
5.7%
B 286
 
4.4%
G 266
 
4.1%
A 227
 
3.5%
C 119
 
1.8%
E 87
 
1.3%
D 87
 
1.3%
R 84
 
1.3%
Other values (5) 215
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
t 368
24.5%
h 368
24.5%
e 368
24.5%
r 368
24.5%
i 10
 
0.7%
s 10
 
0.7%
n 5
 
0.3%
g 5
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 7963
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 2415
30.3%
S 2307
29.0%
O 368
 
4.6%
t 368
 
4.6%
h 368
 
4.6%
e 368
 
4.6%
r 368
 
4.6%
B 286
 
3.6%
G 266
 
3.3%
A 227
 
2.9%
Other values (13) 622
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 2415
30.3%
S 2307
29.0%
O 368
 
4.6%
t 368
 
4.6%
h 368
 
4.6%
e 368
 
4.6%
r 368
 
4.6%
B 286
 
3.6%
G 266
 
3.3%
A 227
 
2.9%
Other values (13) 622
 
7.8%

state_top
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size230.8 KiB
Missing
1133 
CA
708 
Other
585 
NY
380 
TX
142 
Other values (6)
469 

Length

Max length7
Median length5
Mean length4.1714955
Min length2

Characters and Unicode

Total characters14254
Distinct characters21
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMissing
2nd rowMissing
3rd rowCA
4th rowOther
5th rowMissing

Common Values

ValueCountFrequency (%)
Missing 1133
33.2%
CA 708
20.7%
Other 585
17.1%
NY 380
 
11.1%
TX 142
 
4.2%
MA 127
 
3.7%
IL 95
 
2.8%
FL 72
 
2.1%
WA 65
 
1.9%
CO 65
 
1.9%

Length

2023-12-31T13:51:43.370365image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
missing 1133
33.2%
ca 708
20.7%
other 585
17.1%
ny 380
 
11.1%
tx 142
 
4.2%
ma 127
 
3.7%
il 95
 
2.8%
fl 72
 
2.1%
wa 65
 
1.9%
co 65
 
1.9%

Most occurring characters

ValueCountFrequency (%)
i 2266
15.9%
s 2266
15.9%
M 1260
8.8%
n 1133
7.9%
g 1133
7.9%
A 945
 
6.6%
C 773
 
5.4%
O 650
 
4.6%
r 585
 
4.1%
e 585
 
4.1%
Other values (11) 2658
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9138
64.1%
Uppercase Letter 5116
35.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 1260
24.6%
A 945
18.5%
C 773
15.1%
O 650
12.7%
N 380
 
7.4%
Y 380
 
7.4%
L 167
 
3.3%
T 142
 
2.8%
X 142
 
2.8%
I 95
 
1.9%
Other values (3) 182
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
i 2266
24.8%
s 2266
24.8%
n 1133
12.4%
g 1133
12.4%
r 585
 
6.4%
e 585
 
6.4%
h 585
 
6.4%
t 585
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 14254
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2266
15.9%
s 2266
15.9%
M 1260
8.8%
n 1133
7.9%
g 1133
7.9%
A 945
 
6.6%
C 773
 
5.4%
O 650
 
4.6%
r 585
 
4.1%
e 585
 
4.1%
Other values (11) 2658
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2266
15.9%
s 2266
15.9%
M 1260
8.8%
n 1133
7.9%
g 1133
7.9%
A 945
 
6.6%
C 773
 
5.4%
O 650
 
4.6%
r 585
 
4.1%
e 585
 
4.1%
Other values (11) 2658
18.6%

country_top_AU
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3309 
True
 
108
ValueCountFrequency (%)
False 3309
96.8%
True 108
 
3.2%
2023-12-31T13:51:43.486396image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_BR
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3397 
True
 
20
ValueCountFrequency (%)
False 3397
99.4%
True 20
 
0.6%
2023-12-31T13:51:43.585824image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_CA
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3298 
True
 
119
ValueCountFrequency (%)
False 3298
96.5%
True 119
 
3.5%
2023-12-31T13:51:43.684821image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_DE
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3330 
True
 
87
ValueCountFrequency (%)
False 3330
97.5%
True 87
 
2.5%
2023-12-31T13:51:43.786507image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_FR
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3353 
True
 
64
ValueCountFrequency (%)
False 3353
98.1%
True 64
 
1.9%
2023-12-31T13:51:43.884372image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_GB
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3151 
True
 
266
ValueCountFrequency (%)
False 3151
92.2%
True 266
 
7.8%
2023-12-31T13:51:43.996323image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_IN
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3394 
True
 
23
ValueCountFrequency (%)
False 3394
99.3%
True 23
 
0.7%
2023-12-31T13:51:44.101478image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_Missing
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3412 
True
 
5
ValueCountFrequency (%)
False 3412
99.9%
True 5
 
0.1%
2023-12-31T13:51:44.205684image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_NL
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3367 
True
 
50
ValueCountFrequency (%)
False 3367
98.5%
True 50
 
1.5%
2023-12-31T13:51:44.315265image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_Other
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3049 
True
368 
ValueCountFrequency (%)
False 3049
89.2%
True 368
 
10.8%
2023-12-31T13:51:44.414765image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

country_top_US
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
True
2307 
False
1110 
ValueCountFrequency (%)
True 2307
67.5%
False 1110
32.5%
2023-12-31T13:51:44.516897image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_CA
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2709 
True
708 
ValueCountFrequency (%)
False 2709
79.3%
True 708
 
20.7%
2023-12-31T13:51:44.617766image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_CO
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3352 
True
 
65
ValueCountFrequency (%)
False 3352
98.1%
True 65
 
1.9%
2023-12-31T13:51:44.723459image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_FL
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3345 
True
 
72
ValueCountFrequency (%)
False 3345
97.9%
True 72
 
2.1%
2023-12-31T13:51:44.825871image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_GA
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3372 
True
 
45
ValueCountFrequency (%)
False 3372
98.7%
True 45
 
1.3%
2023-12-31T13:51:44.930741image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_IL
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3322 
True
 
95
ValueCountFrequency (%)
False 3322
97.2%
True 95
 
2.8%
2023-12-31T13:51:45.029926image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_MA
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3290 
True
 
127
ValueCountFrequency (%)
False 3290
96.3%
True 127
 
3.7%
2023-12-31T13:51:45.137542image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_Missing
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2284 
True
1133 
ValueCountFrequency (%)
False 2284
66.8%
True 1133
33.2%
2023-12-31T13:51:45.237554image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_NY
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3037 
True
380 
ValueCountFrequency (%)
False 3037
88.9%
True 380
 
11.1%
2023-12-31T13:51:45.380034image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_Other
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2832 
True
585 
ValueCountFrequency (%)
False 2832
82.9%
True 585
 
17.1%
2023-12-31T13:51:45.485216image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_TX
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3275 
True
 
142
ValueCountFrequency (%)
False 3275
95.8%
True 142
 
4.2%
2023-12-31T13:51:45.589972image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

state_top_WA
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3352 
True
 
65
ValueCountFrequency (%)
False 3352
98.1%
True 65
 
1.9%
2023-12-31T13:51:45.695457image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2891 
True
526 
ValueCountFrequency (%)
False 2891
84.6%
True 526
 
15.4%
2023-12-31T13:51:45.803479image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_2. Tech - Software Publisher
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3227 
True
 
190
ValueCountFrequency (%)
False 3227
94.4%
True 190
 
5.6%
2023-12-31T13:51:45.913933image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_3. Finance
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3073 
True
344 
ValueCountFrequency (%)
False 3073
89.9%
True 344
 
10.1%
2023-12-31T13:51:46.020402image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_4. Consulting
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3290 
True
 
127
ValueCountFrequency (%)
False 3290
96.3%
True 127
 
3.7%
2023-12-31T13:51:46.130632image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_5. Retail
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3151 
True
 
266
ValueCountFrequency (%)
False 3151
92.2%
True 266
 
7.8%
2023-12-31T13:51:46.240327image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_6. Manufacturing
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3119 
True
 
298
ValueCountFrequency (%)
False 3119
91.3%
True 298
 
8.7%
2023-12-31T13:51:46.421193image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_7. Wholesale Trade
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3257 
True
 
160
ValueCountFrequency (%)
False 3257
95.3%
True 160
 
4.7%
2023-12-31T13:51:46.524716image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_8. Healthcare
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3282 
True
 
135
ValueCountFrequency (%)
False 3282
96.0%
True 135
 
4.0%
2023-12-31T13:51:46.626556image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_9. Other
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2152 
True
1265 
ValueCountFrequency (%)
False 2152
63.0%
True 1265
37.0%
2023-12-31T13:51:46.727847image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

industry_nan
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3311 
True
 
106
ValueCountFrequency (%)
False 3311
96.9%
True 106
 
3.1%
2023-12-31T13:51:46.828999image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Over 10B
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3321 
True
 
96
ValueCountFrequency (%)
False 3321
97.2%
True 96
 
2.8%
2023-12-31T13:51:47.181143image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Under 100M
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3233 
True
 
184
ValueCountFrequency (%)
False 3233
94.6%
True 184
 
5.4%
2023-12-31T13:51:47.279176image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Under 10B
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3158 
True
 
259
ValueCountFrequency (%)
False 3158
92.4%
True 259
 
7.6%
2023-12-31T13:51:47.376298image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Under 10M
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3379 
True
 
38
ValueCountFrequency (%)
False 3379
98.9%
True 38
 
1.1%
2023-12-31T13:51:47.474085image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Under 1B
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2970 
True
447 
ValueCountFrequency (%)
False 2970
86.9%
True 447
 
13.1%
2023-12-31T13:51:47.576306image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_Under 1M
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
3409 
True
 
8
ValueCountFrequency (%)
False 3409
99.8%
True 8
 
0.2%
2023-12-31T13:51:47.673848image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

revenue_nan
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
True
2385 
False
1032 
ValueCountFrequency (%)
True 2385
69.8%
False 1032
30.2%
2023-12-31T13:51:47.777250image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

founded_After 2000
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2251 
True
1166 
ValueCountFrequency (%)
False 2251
65.9%
True 1166
34.1%
2023-12-31T13:51:47.877182image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

founded_Before 2000
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
False
2991 
True
426 
ValueCountFrequency (%)
False 2991
87.5%
True 426
 
12.5%
2023-12-31T13:51:47.988851image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

founded_nan
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
True
1825 
False
1592 
ValueCountFrequency (%)
True 1825
53.4%
False 1592
46.6%
2023-12-31T13:51:48.088702image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2023-12-31T13:51:48.492260image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
company_revenue_bucketcountry_topcountry_top_AUcountry_top_BRcountry_top_CAcountry_top_DEcountry_top_FRcountry_top_GBcountry_top_INcountry_top_Missingcountry_top_NLcountry_top_Othercountry_top_UScrossbeam_product10_customercrossbeam_product11_customercrossbeam_product12_customercrossbeam_product13_customercrossbeam_product14_customercrossbeam_product15_customercrossbeam_product16_customercrossbeam_product17_customercrossbeam_product18_customercrossbeam_product19_customercrossbeam_product1_customercrossbeam_product20_customercrossbeam_product21_customercrossbeam_product22_customercrossbeam_product23_customercrossbeam_product2_customercrossbeam_product3_customercrossbeam_product4_customercrossbeam_product5_customercrossbeam_product6_customercrossbeam_product7_customercrossbeam_product8_customercrossbeam_product9_customerdnb_founded_time_groupedfounded_After 2000founded_Before 2000founded_nanhas_crossbeam_datahas_hg_datahg_product_100hg_product_101hg_product_102hg_product_103hg_product_104hg_product_105hg_product_106hg_product_107hg_product_108hg_product_109hg_product_110hg_product_111hg_product_112hg_product_113hg_product_114hg_product_115hg_product_116hg_product_117hg_product_118hg_product_119hg_product_120hg_product_121hg_product_122hg_product_123hg_product_124hg_product_125hg_product_126hg_product_127hg_product_128hg_product_129hg_product_130hg_product_131hg_product_132hg_product_133hg_product_134hg_product_135hg_product_136hg_product_137hg_product_138hg_product_139hg_product_140hg_product_141hg_product_142hg_product_143hg_product_144hg_product_145hg_product_146hg_product_147hg_product_148hg_product_27hg_product_28hg_product_29hg_product_30hg_product_31hg_product_32hg_product_33hg_product_34hg_product_35hg_product_36hg_product_37hg_product_38hg_product_39hg_product_40hg_product_41hg_product_42hg_product_43hg_product_44hg_product_45hg_product_46hg_product_47hg_product_48hg_product_49hg_product_50hg_product_51hg_product_52hg_product_53hg_product_54hg_product_55hg_product_56hg_product_57hg_product_58hg_product_59hg_product_60hg_product_61hg_product_62hg_product_63hg_product_64hg_product_65hg_product_66hg_product_67hg_product_68hg_product_69hg_product_70hg_product_71hg_product_72hg_product_73hg_product_74hg_product_75hg_product_76hg_product_77hg_product_78hg_product_79hg_product_80hg_product_81hg_product_82hg_product_83hg_product_84hg_product_85hg_product_86hg_product_87hg_product_88hg_product_89hg_product_90hg_product_91hg_product_92hg_product_93hg_product_94hg_product_95hg_product_96hg_product_97hg_product_98hg_product_99industry_1. Tech - Computer systems design and related servicesindustry_2. Tech - Software Publisherindustry_3. Financeindustry_4. Consultingindustry_5. Retailindustry_6. Manufacturingindustry_7. Wholesale Tradeindustry_8. Healthcareindustry_9. Otherindustry_groupedindustry_nanis_self_servicerevenue_Over 10Brevenue_Under 100Mrevenue_Under 10Brevenue_Under 10Mrevenue_Under 1Brevenue_Under 1Mrevenue_nanstatestate_topstate_top_CAstate_top_COstate_top_FLstate_top_GAstate_top_ILstate_top_MAstate_top_Missingstate_top_NYstate_top_Otherstate_top_TXstate_top_WA
company_revenue_bucket1.0000.0300.0000.0000.0000.0460.0960.0760.0001.0000.0000.0360.0670.0860.0580.0440.0510.0850.0500.0490.0630.0310.1320.0670.0590.1100.0830.0630.0110.1100.0400.1490.1200.1330.0300.0550.2780.1210.2540.1330.0690.1430.1530.1990.3060.2410.1530.2210.1020.1060.0960.0600.0860.0600.2070.0960.1990.0550.1560.0920.0530.1970.1020.0710.0960.0760.2680.1610.0750.0790.0530.1350.0940.1920.2920.1360.0740.0660.0720.1130.1340.1590.1330.1500.0590.2610.1900.0770.0750.0530.0500.0960.1480.1200.1140.1480.1340.2140.1940.0850.1970.1960.2430.2570.0890.2590.2210.1420.2530.2170.1300.1550.1190.1140.1210.1410.1280.1580.0610.0810.0720.1060.0590.0960.0960.0830.2090.2650.1180.2530.0690.1450.1590.1030.1140.0880.1190.2150.1540.1940.2700.2270.1740.2280.1650.2000.0960.2050.1570.0530.1610.1570.1020.0600.1080.0530.1450.0960.0710.1730.2400.0870.1460.1470.1940.0890.0270.0710.0000.2250.0430.0470.0710.1381.0000.0270.9980.9980.9980.9980.9980.9981.0000.0000.0460.0630.0000.0630.0000.0000.0000.0580.0150.1090.0270.000
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hg_product_450.2170.0950.0160.0000.0390.0000.0110.0610.0350.0120.0530.0680.1290.0800.0160.1010.0640.0930.0340.0480.0820.0430.2150.0870.0760.0500.0710.0350.0780.0240.0220.1470.2260.0980.1240.0490.3070.0000.2850.2040.0220.9670.7160.7200.7480.7370.7130.7360.7120.7131.0000.7080.7090.7080.7411.0000.7300.7110.7170.7130.7080.7270.7110.7071.0000.7180.7550.7440.7150.7110.7070.7290.7080.7110.7440.7090.7100.7080.7080.7130.7130.7440.7480.7250.7070.7580.7600.7290.7090.7070.7071.0000.7480.7240.7260.7700.7350.7760.7620.7240.7580.7430.7620.7910.7130.7800.7590.7150.7661.0000.7110.7290.7180.7210.7390.7340.7140.7200.7070.7280.7080.7250.7080.7070.7080.7080.7290.7410.7100.7370.7200.7370.7330.7360.7290.7150.7200.7380.7200.7290.7370.7400.7210.7380.7220.7331.0000.7500.7240.7080.7190.7430.7220.7140.7130.7080.7141.0000.7070.7270.7460.7120.7150.7160.0920.0440.0460.0340.0260.1260.0000.0310.0300.1180.1200.2050.2980.3290.3850.1490.4790.0740.8270.0680.1080.0580.0000.0090.0230.0270.0160.1270.0780.0510.0210.026
hg_product_460.1300.0970.0180.0860.0360.0000.0000.0000.0830.0120.0430.0350.0680.0720.0350.0750.1480.0880.0300.0610.0800.0740.1490.0860.0680.0370.0590.0080.0670.0310.0580.1150.1350.1530.1140.1850.3070.0000.2870.2060.0460.9660.7080.7160.7090.7100.7090.7100.7120.7251.0000.7070.7140.7350.7081.0000.7080.7070.7090.7110.7070.7100.7070.7071.0000.7110.7090.7080.7080.7080.7070.7070.7130.7110.7100.7070.7120.7070.7070.7080.7090.7080.7080.7070.7090.7090.7080.7090.7070.7110.7071.0000.7090.7070.7070.7080.7080.7080.7080.7080.7080.7090.7100.7090.7100.7130.7100.7080.7130.7111.0000.7080.7070.7070.7080.7080.7070.7080.7070.7080.7180.7080.7070.7070.7100.7070.7100.7110.7070.7190.7070.7070.7110.7070.7070.7080.7070.7070.7110.7080.7100.7100.7090.7120.7090.7121.0000.7080.7150.7350.7130.7070.7090.7070.7100.7070.7091.0000.7070.7090.7140.7100.7090.7080.0890.0430.0530.0330.0160.1180.0030.0000.0210.1110.1200.2040.2430.3190.3660.1490.4740.0640.8250.0000.0650.0380.0000.0000.0000.0460.0000.0640.0610.0380.0000.000
hg_product_470.1550.1030.0460.0000.0410.0000.0000.0350.0340.0120.0450.1010.1220.0870.0270.0850.0590.0930.0390.0490.0750.0470.1530.0800.0770.0360.0520.0640.0670.0330.0360.1150.1360.0960.1180.0560.3190.0380.2920.2040.0340.9670.7130.7090.7180.7140.7080.7110.7080.7101.0000.7070.7090.7070.7141.0000.7130.7070.7080.7070.7070.7120.7110.7071.0000.7110.7200.7460.7080.7100.7070.7430.7080.7090.7190.7070.7090.7070.7070.7100.7090.7330.7390.7130.7130.7270.7440.7570.7090.7120.7081.0000.7340.7160.7130.7480.7400.7360.7520.7100.7330.7180.7170.7190.7100.7160.7150.7100.7190.7290.7081.0000.7700.7230.7470.7220.7160.7100.7080.7380.7080.7270.7070.7070.7090.7070.7160.7210.7080.7140.7200.7480.7280.7320.7210.7110.7670.7290.7100.7150.7190.7160.7130.7160.7130.7161.0000.7550.7110.7070.7130.7520.7300.7140.7180.7070.7071.0000.7070.7100.7170.7100.7070.7120.0900.0520.0820.0330.0180.1210.0000.0000.0090.1210.1210.2030.2090.3280.3780.1480.4900.0730.8260.0620.0970.0510.0120.0000.0000.0310.0000.1190.0790.0440.0000.008
hg_product_480.1190.1010.0480.0000.0530.0000.0000.0190.0400.0120.0460.0880.1280.0780.0240.0770.0550.0890.0400.0420.0780.0460.1510.0790.0720.0360.0470.0360.0740.0290.0460.1180.1330.0940.1200.0500.3080.0000.2860.2050.0330.9670.7090.7090.7160.7120.7070.7120.7080.7081.0000.7070.7070.7070.7121.0000.7110.7070.7070.7080.7070.7100.7080.7071.0000.7120.7190.7470.7080.7080.7070.7610.7070.7070.7120.7080.7070.7070.7070.7090.7080.7220.7410.7100.7110.7210.7400.7340.7090.7090.7071.0000.7240.7110.7110.7390.7320.7340.7370.7090.7190.7120.7130.7150.7080.7120.7140.7070.7120.7180.7070.7701.0000.7160.7360.7140.7100.7100.7080.7300.7070.7240.7070.7070.7080.7070.7120.7150.7070.7110.7120.7660.7150.7290.7130.7090.7230.7320.7080.7110.7130.7140.7120.7120.7100.7121.0000.7500.7100.7070.7090.7550.7270.7120.7140.7070.7071.0000.7070.7090.7170.7070.7080.7090.0890.0520.0480.0320.0220.1190.0000.0000.0250.1120.1210.2030.1940.3230.3720.1490.4820.0990.8270.0940.1040.0650.0000.0130.0000.0340.0000.1240.0810.0560.0000.000
hg_product_490.1140.0730.0150.0000.0420.0000.0000.0040.0760.0120.0420.0340.0680.0670.0190.0800.0500.1000.0340.0360.0750.0430.1470.0910.0680.0070.0500.0120.0630.0220.0080.1230.1330.1030.1140.0460.3130.0130.2900.2040.0200.9660.7140.7130.7220.7340.7090.7140.7170.7151.0000.7090.7140.7120.7171.0000.7140.7080.7140.7100.7070.7160.7140.7071.0000.7110.7240.7120.7230.7200.7070.7130.7080.7100.7180.7070.7140.7070.7080.7110.7090.7130.7120.7170.7070.7260.7150.7150.7070.7070.7071.0000.7170.7140.7190.7140.7120.7200.7200.7100.7170.7180.7170.7220.7100.7190.7210.7150.7190.7210.7070.7230.7161.0000.7330.7230.7210.7120.7070.7150.7080.7110.7070.7070.7090.7070.7150.7200.7090.7330.7150.7170.7270.7130.7180.7140.7300.7160.7160.7230.7210.7260.7140.7190.7190.7171.0000.7200.7130.7080.7130.7170.7100.7080.7100.7070.7111.0000.7080.7130.7250.7100.7110.7140.0980.0500.0450.0340.0350.1250.0000.0000.0220.1190.1200.2050.2180.3190.3690.1490.4760.0740.8250.0530.0620.0360.0000.0000.0000.0280.0000.0640.0640.0450.0000.000
hg_product_500.1210.0720.0250.0000.0340.0000.0000.0000.0260.0120.0420.0730.0840.0920.0210.0810.0580.0920.0540.0460.0740.0450.1650.0860.0720.0310.0610.0580.0690.0290.0300.1290.1380.0930.1190.0510.3170.0660.2860.2090.0280.9670.7140.7140.7230.7210.7090.7160.7090.7111.0000.7070.7070.7080.7201.0000.7150.7100.7090.7110.7070.7160.7080.7071.0000.7170.7260.7510.7100.7090.7070.7360.7080.7100.7150.7080.7100.7070.7080.7100.7090.7420.7470.7170.7150.7330.7530.7460.7120.7100.7071.0000.7360.7120.7140.7720.7280.7600.7630.7100.7350.7270.7190.7210.7080.7200.7200.7100.7270.7390.7080.7470.7360.7331.0000.7600.7170.7100.7100.7220.7070.7220.7070.7080.7080.7070.7220.7220.7080.7210.7210.7480.7240.7270.7250.7120.7390.7220.7100.7150.7170.7200.7180.7190.7200.7221.0000.7550.7190.7080.7160.7490.7300.7110.7180.7070.7111.0000.7070.7180.7240.7130.7150.7130.0950.0530.0460.0320.0190.1250.0000.0170.0080.1180.1200.2040.2190.3180.3690.1490.4770.0810.8250.0880.0880.0630.0000.0270.0000.0270.0000.0800.0810.0390.0330.000
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hg_product_930.0960.0830.0210.0000.0360.0000.0000.0000.0240.0080.0420.0340.0690.0970.0300.1060.0730.1180.0470.0530.1050.0630.2070.1100.0980.0240.0650.0230.0910.0380.0250.1610.1880.1300.1620.0690.3070.0000.2850.2040.0240.9661.0001.0001.0001.0001.0001.0001.0001.0000.9991.0001.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0890.0430.0460.0350.0190.1180.0000.0000.0180.1590.1200.2030.1890.3170.3640.1460.4720.0600.8250.0970.0970.0380.0000.0000.0000.0300.0000.0650.0610.0410.0060.000
hg_product_940.0710.0470.0160.0000.0350.0000.0000.0000.0230.0120.0420.0320.0710.0720.0130.0730.0490.0820.0290.0340.1570.0410.1490.1760.0690.0030.0430.0230.0620.0210.0040.1130.1330.0910.1150.1630.3110.0040.2900.2050.0200.9660.7110.7200.7080.7080.7070.7120.7220.7071.0000.7070.7070.7900.7131.0000.7080.7070.7070.7210.7070.7120.7070.7071.0000.7080.7080.7070.7100.7110.7070.7070.7070.7070.7100.7240.7240.7070.7070.7270.7070.7080.7070.7070.7070.7070.7070.7070.7070.7070.7071.0000.7070.7090.7090.7070.7070.7080.7070.7130.7070.7080.7070.7070.7160.7070.7070.7070.7070.7070.7070.7070.7070.7080.7070.7080.7070.7100.7070.7080.7070.7090.7070.7070.7070.7070.7080.7090.7070.7080.7080.7070.7110.7080.7070.7070.7070.7070.7100.7080.7070.7070.7090.7080.7090.7081.0000.7070.7190.7070.7070.7070.7070.7070.7080.7070.7161.0001.0000.7090.7100.7170.7140.7130.0890.0610.0450.0320.0130.1220.0000.0000.0210.1140.1200.2030.1910.3180.3720.1480.4740.0640.8250.0570.0720.0370.0000.0000.0000.0270.0000.0670.0600.0420.0540.000
hg_product_950.1730.0630.0150.0000.0370.0000.0000.0300.0400.0120.0430.0400.0770.0690.0260.0930.0710.1220.0350.0390.0820.0630.1530.0980.0710.0240.0510.0180.0650.0290.0330.1210.1350.1190.1150.0640.3190.0340.2930.2040.0440.9660.7400.7380.7400.7870.7330.7930.7330.7091.0000.7120.7210.7160.7701.0000.7770.7130.7360.7190.7070.8060.7160.7131.0000.7100.7410.7170.7280.7230.7070.7110.7080.7240.7320.7220.7130.7070.7090.7440.7230.7180.7140.7530.7070.7370.7160.7110.7070.7070.7071.0000.7340.7250.7370.7190.7130.7270.7170.7120.7230.7280.7350.7330.7310.7360.7330.7240.7380.7270.7090.7100.7090.7130.7180.7320.7170.7290.7070.7130.7100.7100.7080.7070.7100.7070.7540.7510.7090.7490.7070.7120.7390.7120.7140.7100.7090.7150.7420.7450.7410.7500.7390.7340.7250.7341.0000.7210.7320.7160.7110.7180.7090.7070.7080.7120.7461.0000.7091.0000.7540.7150.7370.7360.0910.0620.0680.0320.0130.1340.0000.0000.0280.1270.1200.2030.2780.3240.3700.1480.4770.0680.8260.0750.0730.0430.0000.0000.0000.0280.0000.0740.0600.0560.0000.023
hg_product_960.2400.0810.0160.0000.0350.0160.0050.0540.0270.0120.0480.0460.1070.0690.0230.0890.0660.1180.0300.0340.0820.0520.1800.0910.0770.0160.0660.0090.0630.0260.0080.1300.1450.1110.1140.0810.3350.0690.2980.2040.0200.9660.7450.7920.7830.7960.7350.7900.7190.7241.0000.7090.7140.7100.7951.0000.7930.7110.7290.7200.7070.7850.7140.7091.0000.7160.7890.7310.7380.7280.7070.7190.7150.7150.7510.7200.7140.7070.7100.7180.7110.7350.7290.7410.7090.7600.7350.7110.7070.7070.7071.0000.7510.7200.7490.7330.7260.7500.7370.7140.7510.7470.7400.7480.7120.7530.7540.7190.7440.7460.7140.7170.7170.7250.7240.7280.7120.7200.7070.7180.7080.7220.7080.7070.7070.7070.7690.7810.7120.7760.7090.7220.7430.7250.7240.7130.7120.7330.7410.7660.7650.7770.7420.7540.7400.7481.0000.7390.7290.7100.7140.7310.7140.7120.7100.7090.7291.0000.7100.7541.0000.7210.7340.7260.0920.0530.0710.0320.0270.1500.0000.0000.0330.1350.1200.2060.3080.3370.3990.1500.4820.0730.8270.0710.0880.0350.0000.0000.0210.0420.0210.1040.0630.0540.0000.000
hg_product_970.0870.0570.0210.0000.0350.0000.0000.0000.0490.0120.0440.0310.0680.0690.0130.0800.0950.1010.0300.0340.0960.0460.1490.1070.0680.0290.0470.0090.0630.0230.0330.1340.1340.0990.1140.0670.3100.0160.2860.2040.0290.9660.7380.7160.7140.7190.7200.7380.7140.7341.0000.7280.7170.7490.7251.0000.7310.7070.7100.7500.7070.7340.7130.7071.0000.7090.7140.7090.7210.7100.7070.7080.7160.7080.7160.7070.7250.7070.7070.7360.7070.7110.7080.7330.7080.7130.7100.7120.7070.7090.7071.0000.7190.7320.7320.7100.7080.7110.7090.7240.7150.7200.7130.7170.7480.7220.7150.7330.7190.7120.7100.7100.7070.7100.7130.7170.7220.7220.7070.7090.7230.7160.7070.7070.7120.7070.7240.7180.7070.7310.7100.7080.7160.7090.7110.7080.7140.7090.7310.7270.7200.7170.7260.7210.7180.7221.0000.7090.7240.7170.7200.7100.7110.7120.7120.7070.7161.0000.7170.7150.7211.0000.7370.7320.0910.0420.0460.0480.0210.1260.0000.0000.0100.1160.1200.2030.2040.3190.3670.1500.4740.0650.8250.0750.0640.0350.0000.0000.0000.0280.0230.0640.0600.0390.0000.000
hg_product_980.1460.0550.0150.0000.0340.0000.0000.0000.0390.0120.0450.0330.0710.0670.0150.0960.0560.0920.0310.0370.0860.0620.1580.0950.0680.0530.0720.0030.0620.0220.0260.1240.1400.1030.1130.0590.3110.0050.2880.2040.0240.9660.7320.7510.7190.7320.7270.7320.7260.7111.0000.7070.7080.7350.7391.0000.7320.7160.7290.7350.7070.7450.7110.7071.0000.7130.7190.7090.7290.7180.7070.7080.7080.7240.7200.7190.7120.7070.7140.7250.7120.7090.7080.7270.7090.7170.7100.7080.7070.7070.7071.0000.7150.7190.7220.7110.7080.7140.7100.7130.7150.7220.7180.7210.7330.7190.7180.7230.7200.7150.7090.7070.7080.7110.7150.7180.7090.7360.7070.7090.7090.7120.7070.7070.7100.7070.7350.7220.7080.7240.7100.7090.7170.7090.7150.7130.7100.7110.7270.7280.7190.7280.7210.7360.7130.7181.0000.7120.7170.7140.7090.7090.7100.7080.7070.7070.7411.0000.7140.7370.7340.7371.0000.7450.0920.0430.0500.0330.0130.1320.0000.0000.0180.1180.1200.2030.2450.3190.3670.1510.4800.0650.8250.0990.0850.0460.0000.0000.0000.0290.0320.0680.0600.0490.0000.065
hg_product_990.1470.0660.0250.0000.0410.0000.0000.0000.0360.0120.0450.0480.0850.0710.0270.0940.0790.1250.0380.0430.0980.0490.1510.0850.0710.0360.0580.0240.0670.0320.0330.1240.1340.1030.1160.0610.3120.0090.2890.2040.0580.9670.7400.7270.7220.7410.7180.7370.7160.7311.0000.7070.7080.7310.7501.0000.7310.7070.7190.7420.7070.7310.7220.7071.0000.7110.7210.7110.7210.7100.7070.7090.7180.7150.7270.7110.7110.7070.7070.7480.7200.7120.7120.7470.7070.7270.7110.7090.7070.7070.7071.0000.7200.7340.7400.7100.7100.7160.7130.7160.7180.7260.7150.7200.7840.7240.7210.7500.7250.7160.7080.7120.7090.7140.7130.7240.7230.7720.7070.7120.7090.7150.7070.7070.7130.7070.7330.7300.7070.7410.7100.7090.7220.7130.7130.7100.7090.7100.7190.7380.7320.7330.7620.7330.7220.7301.0000.7150.7180.7130.7110.7120.7090.7090.7080.7070.7281.0000.7130.7360.7260.7320.7451.0000.0920.0500.0470.0330.0180.1590.0000.0000.0210.1330.1200.2030.2470.3190.3650.1480.4790.0660.8250.1130.0910.0390.0000.0000.0400.0290.0250.0830.0620.0490.0000.059
industry_1. Tech - Computer systems design and related services0.1940.0670.0000.0210.0270.0440.0220.0000.0090.0000.0000.0000.0210.1610.0210.0270.0230.0310.0660.0000.0170.0000.0000.0130.0000.0380.0000.1120.0000.0930.0300.0430.0000.0300.0000.0150.1920.1360.1020.0580.0000.0940.0940.0910.0980.0910.0880.0920.0900.0900.0890.0880.0890.0890.0940.0890.0930.0890.0890.0900.0880.0910.0900.0890.0890.1090.0990.0990.0910.0890.0890.0880.0900.0900.1040.0900.0900.0880.0890.0880.0890.0890.0880.0880.0930.0930.0900.1030.0960.0920.0970.0890.0960.0910.0930.0910.0890.0930.0920.0900.0890.0890.0940.0890.0890.0900.0920.0910.0890.0920.0890.0900.0890.0980.0950.0910.0910.0920.0900.1060.0890.0960.0890.0920.0880.0880.0910.0900.0890.0940.0890.0910.0890.1270.0880.0880.0880.0960.0930.0950.0960.0930.0950.0980.0910.0900.0890.0920.0880.0890.0880.0910.1240.1010.1040.0880.0910.0890.0890.0910.0920.0910.0920.0921.0000.1000.1400.0800.1210.1290.0910.0830.3260.9990.0720.0170.0530.0240.0880.0000.0560.0000.0940.0610.0760.0520.0000.0260.0000.0000.0000.0170.0120.0610.0000.000
industry_2. Tech - Software Publisher0.0890.0840.0190.0000.0110.0000.0330.0360.0000.0000.0170.0460.0610.1470.0390.0420.0100.0580.0000.0690.0430.0230.0740.0450.0890.0560.0000.1010.0410.0510.0000.0200.0690.0110.0840.0310.0170.0750.0000.0770.0000.0310.0430.0420.0480.0560.0430.0580.0450.0450.0430.0420.0440.0420.0570.0430.0620.0430.0420.0450.0420.0520.0430.0420.0430.0530.0450.0870.0440.0430.0420.0660.0440.0420.0540.0520.0450.0420.0420.0420.0430.0670.0740.0530.0650.0420.0690.1160.0860.0730.0440.0430.0800.0530.0420.0810.0820.0830.0950.0600.0480.0440.0600.0620.0430.0600.0450.0420.0540.0440.0430.0520.0520.0500.0530.0420.0420.0430.0520.0670.0690.0750.0430.0420.0450.0810.0690.0670.0440.0550.0490.0690.0420.1390.0420.0470.0550.0450.0500.0650.0680.0620.0420.0550.0460.0520.0430.0770.0420.0420.0420.0810.1220.0920.0650.0420.0480.0430.0610.0620.0530.0420.0430.0500.1001.0000.0770.0410.0660.0710.0480.0430.1840.9990.0360.0570.0000.0070.0000.0000.0920.0000.0680.0490.1030.0840.0000.0140.0000.0000.0400.0560.0260.0000.0000.004
industry_3. Finance0.0270.0310.0330.0080.0000.0110.0000.0000.0130.0000.0000.0000.0000.0730.0000.0000.0000.0000.0190.0000.0240.0000.0170.0190.0400.0190.0000.1110.0000.0270.0220.1130.0000.0520.0000.0280.0580.0420.0230.0150.0000.0470.0450.0550.0560.0640.0460.0530.0640.0510.0460.0450.0600.0450.0700.0460.0530.0530.0450.0450.0450.0510.0560.0460.0460.0530.0710.0490.0580.0660.0450.0490.0440.0500.0570.0460.0440.0450.0450.0450.0450.0550.0580.0440.0490.0490.0720.0740.0470.0510.0440.0460.0460.0460.0550.0450.0480.0580.0570.0470.0530.0580.0880.0540.0470.0520.0720.0440.0580.0460.0530.0820.0480.0450.0460.0450.0450.0460.0440.0480.0470.0460.0460.0450.0520.0450.0880.1030.0480.0760.0560.0590.0450.0480.0450.0450.0510.0750.0660.0640.0690.0890.0660.0860.0450.0670.0460.0450.0520.0450.0460.0460.0810.0590.0560.0450.0570.0460.0450.0680.0710.0460.0500.0470.1400.0771.0000.0610.0940.1000.0700.0630.2550.9990.0540.0370.0000.0000.0300.0130.0410.0000.0560.0310.0370.0360.0230.0000.0190.0000.0080.0000.0000.0100.0000.000
industry_4. Consulting0.0710.0430.0140.0000.0180.0000.0000.0260.0000.0000.0040.0000.0530.0000.0000.0000.0210.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0600.0000.0500.0390.0000.0320.0350.0330.0370.0330.0330.0360.0330.0330.0350.0320.0330.0320.0330.0350.0330.0330.0340.0330.0320.0330.0330.0330.0350.0460.0340.0380.0400.0320.0690.0330.0330.0330.0330.0330.0330.0320.0320.0470.0340.0380.0370.0370.0320.0320.0330.0350.0320.0340.0330.0350.0360.0320.0430.0320.0340.0340.0340.0350.0330.0340.0360.0320.0340.0330.0340.0320.0360.0340.0330.0330.0320.0340.0320.0320.0340.0410.0390.0330.0330.0330.0330.0320.0350.0320.0330.0330.0330.0340.0330.0340.0340.0330.0370.0320.0350.0480.0390.0380.0400.0320.0340.0360.0390.0350.0350.0340.0330.0320.0320.0360.0330.0330.0350.0320.0340.0350.0320.0320.0320.0480.0330.0330.0800.0410.0611.0000.0510.0550.0360.0320.1480.9990.0250.0000.0230.0000.0310.0000.0330.0000.0540.0000.0550.0210.0000.0000.0000.0000.0000.0550.0000.0270.0020.013
industry_5. Retail0.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0560.0180.0000.0000.0070.0340.0000.0060.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0370.0000.0000.0000.0080.0000.0000.0160.0120.0170.0140.0130.0130.0180.0190.0190.0190.0120.0170.0130.0210.0190.0150.0160.0140.0120.0120.0220.0210.0140.0190.0270.0240.0450.0120.0180.0130.0170.0170.0250.0240.0290.0180.0120.0130.0280.0150.0130.0140.0120.0120.0290.0350.0130.0180.0130.0160.0190.0310.0140.0370.0230.0360.0560.0210.0260.0150.0230.0270.0210.0120.0260.0120.0130.0280.0260.0160.0180.0220.0350.0190.0120.0190.0230.0130.0330.0150.0340.0150.0130.0200.0120.0230.0130.0160.0360.0220.0160.0350.0440.0130.0120.0370.0170.0330.0140.0120.0200.0120.0200.0320.0120.0190.0150.0130.0130.0190.0180.0280.0170.0170.0120.0280.0190.0130.0130.0270.0210.0130.0180.1210.0660.0940.0511.0000.0860.0590.0530.2210.9990.0460.0000.0000.0000.0000.0000.0000.0000.0000.0200.0520.0000.0000.0000.0230.0000.0000.0000.0000.0040.0000.057
industry_6. Manufacturing0.2250.0230.0000.0000.0000.0110.0000.0190.0080.0000.0000.0000.0210.0460.0240.0500.0140.0440.0230.0220.0420.0120.0750.0570.0110.0110.0260.0410.0150.0430.0390.0440.0240.0570.0290.0240.1900.0360.1570.0640.0000.1210.1210.1300.1580.1480.1190.1500.1270.1250.1180.1180.1340.1390.1370.1180.1510.1180.1220.1320.1180.1410.1850.1200.1180.1200.1470.1190.1180.1190.1190.1280.1310.1410.2420.1190.1290.1290.1390.1370.1260.1190.1210.1340.1200.1280.1220.1190.1220.1180.1180.1180.1180.1430.1290.1180.1180.1190.1180.1240.1200.1310.1370.1450.1430.1310.1280.1250.1310.1260.1180.1210.1190.1250.1250.1190.1190.1210.1190.1180.1180.1200.1190.1190.1270.1180.1240.1340.1210.1370.1210.1210.1220.1180.1260.1260.1200.1400.1430.1380.1420.1400.1470.1250.1200.1240.1180.1210.1180.1220.1200.1190.1220.1180.1190.1180.1180.1180.1220.1340.1500.1260.1320.1590.1290.0710.1000.0550.0861.0000.0640.0580.2350.9990.0490.0310.1320.0190.1520.0000.0270.0000.1450.1300.0810.0000.0350.0000.0000.0000.0000.0260.0140.0770.0000.000
industry_7. Wholesale Trade0.0430.0580.0000.0000.0000.0350.0000.0430.0170.0000.0000.0000.0140.0370.0000.0000.0000.0000.0500.0190.0000.0000.0000.0000.0000.0120.0000.0000.0000.0340.0000.0180.0000.0000.0060.0000.0510.0050.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0120.0160.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0170.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0460.0000.0000.0000.0000.0000.0740.0000.0000.0000.0000.0000.0000.0000.0000.0910.0480.0700.0360.0590.0641.0000.0380.1680.9990.0310.0000.0180.0000.0080.0000.0000.0000.0000.1090.0510.0090.0000.0110.0000.0000.0190.0180.0000.0410.0000.018
industry_8. Healthcare0.0470.0460.0000.0000.0000.0220.0000.0000.0000.0000.0070.0350.0530.0000.0000.0000.0000.0000.0290.0000.0000.0000.0210.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0500.0000.0000.0460.0290.0680.0000.0000.0000.0000.0400.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0400.0000.0110.0480.0000.0000.0000.0000.0130.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0310.0000.0000.0000.0000.0000.0330.0000.0000.0000.0280.0000.0250.0000.0410.0000.0000.0000.0000.0000.0000.0000.0010.0310.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0350.0000.0000.0000.0340.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0360.0120.0000.0000.0040.0000.0130.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0830.0430.0630.0320.0530.0580.0381.0000.1530.9990.0270.0000.0000.0000.0280.0000.0000.0000.0330.0000.0750.0000.0000.0220.0000.0000.0000.0560.0570.0000.0130.015
industry_9. Other0.0710.0930.0000.0000.0000.0000.0000.0750.0000.0000.0370.0360.0690.0440.0190.0140.0000.0000.0000.0090.0470.0000.0560.0110.0320.0120.0000.0000.0000.0000.0000.0000.0000.0270.0050.0000.0000.0000.0000.0000.0000.0200.0110.0190.0200.0350.0230.0230.0250.0100.0180.0230.0270.0210.0200.0180.0210.0120.0080.0100.0230.0120.0630.0080.0180.0100.0080.0440.0120.0250.0090.0610.0100.0190.0230.0220.0150.0160.0210.0130.0310.0450.0480.0100.0140.0270.0510.0370.0470.0470.0240.0180.0220.0170.0080.0250.0220.0500.0530.0080.0320.0220.0170.0340.0340.0100.0200.0170.0140.0300.0210.0090.0250.0220.0080.0240.0200.0230.0120.0370.0170.0380.0110.0090.0110.0160.0090.0390.0190.0240.0160.0650.0110.0770.0150.0090.0090.0270.0340.0150.0350.0270.0490.0280.0230.0210.0180.0350.0080.0210.0120.0380.0410.0330.0310.0160.0210.0180.0210.0280.0330.0100.0180.0210.3260.1840.2550.1480.2210.2350.1680.1531.0000.9990.1340.0120.0190.0000.0000.0390.0000.0000.0000.0240.0830.0390.0230.0000.0000.0000.0170.0770.0000.0330.0000.018
industry_grouped0.1380.0540.0380.0200.0140.0630.0300.0910.0410.0000.0390.0620.1170.1650.0260.0390.0000.0430.0660.0430.0450.0000.0780.0470.0680.0430.0000.1280.0000.0780.0170.0840.0380.0510.0740.0200.2720.1610.1930.1350.0000.1590.1120.1170.1400.1320.1090.1310.1190.1140.1590.1080.1210.1190.1280.1590.1320.1100.1100.1160.1080.1240.1510.1130.1590.1260.1370.1320.1130.1150.1160.1250.1150.1220.1880.1130.1140.1130.1190.1220.1140.1220.1220.1200.1170.1170.1310.1420.1270.1200.1120.1590.1260.1250.1220.1220.1250.1320.1340.1160.1170.1180.1350.1300.1230.1210.1210.1140.1220.1180.1110.1210.1120.1190.1180.1100.1100.1140.1110.1240.1150.1230.1110.1090.1150.1170.1290.1410.1110.1300.1150.1270.1120.1630.1130.1130.1150.1320.1320.1300.1350.1360.1320.1290.1140.1190.1590.1250.1100.1160.1100.1230.1550.1300.1230.1200.1160.1590.1140.1270.1350.1160.1180.1330.9990.9990.9990.9990.9990.9990.9990.9990.9991.0001.0000.0670.1440.0000.1760.0370.1190.0000.1960.0640.0720.1100.0420.0380.0310.0000.0430.1210.0600.1110.0000.069
industry_nan1.0000.1760.0220.0380.0000.0000.0000.0000.0000.1470.0000.0000.0000.0810.0750.0740.0710.0740.0700.0760.0730.0710.0800.0730.0940.0720.0730.0820.0750.0740.0720.0740.0840.0730.0840.0711.0000.1260.0630.1650.0650.1160.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1210.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1210.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1210.1210.1200.1200.1200.1200.1200.1200.1210.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1210.1200.1200.1200.1200.1200.1200.1200.1200.1200.1210.1200.1200.1200.1200.1210.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.1200.0720.0360.0540.0250.0460.0490.0310.0270.1341.0001.0000.1740.0190.0350.0450.0000.0650.0000.1150.1100.0220.0150.0000.0340.0000.0000.0000.0000.0000.0000.0000.000
is_self_service0.0270.1160.0000.0560.0000.0590.0230.0360.0000.0150.0000.0590.0610.1030.0960.0870.0820.0870.0830.1080.0910.0820.1230.0940.2170.0910.0900.0900.0960.0990.0830.0990.0930.0910.1250.0840.0920.0310.0930.0960.0830.2030.2030.2030.2060.2040.2030.2030.2030.2030.2030.2030.2030.2040.2050.2030.2030.2030.2030.2030.2030.2030.2030.2030.2030.2050.2050.2050.2040.2030.2040.2080.2030.2030.2050.2030.2030.2030.2030.2030.2030.2100.2130.2030.2030.2050.2050.2030.2030.2030.2030.2030.2050.2040.2030.2050.2090.2060.2070.2030.2070.2030.2030.2030.2030.2030.2080.2030.2030.2050.2040.2030.2030.2050.2040.2040.2030.2030.2030.2030.2030.2030.2030.2030.2030.2030.2030.2050.2030.2030.2030.2090.2030.2050.2030.2030.2030.2050.2040.2030.2030.2050.2040.2040.2050.2040.2030.2060.2030.2040.2030.2070.2040.2030.2030.2030.2030.2030.2030.2030.2060.2030.2030.2030.0170.0570.0370.0000.0000.0310.0000.0000.0120.0670.1741.0000.0640.0600.1120.0260.1140.0000.2150.1090.0740.0280.0140.0270.0000.0000.0260.0600.0000.0320.0090.000
revenue_Over 10B0.9980.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0120.0410.0460.0670.1050.0110.0220.0990.0100.1340.0830.0350.0640.0800.0110.0100.0340.0170.2150.1710.2000.0190.0890.2390.0620.2170.0790.0110.1700.2650.3100.3160.3310.2630.3160.2150.2270.1890.1900.2100.1910.3060.1890.2870.1920.2710.2010.1900.2800.2090.1960.1890.1910.3020.2270.1920.1980.1910.2140.2070.3100.3750.2570.1950.1900.2000.2250.2300.2350.2100.2570.1910.3290.2400.1940.1940.1900.1910.1890.2450.2250.2090.2360.2070.2760.2530.2060.2590.2960.3220.3400.2110.3770.3200.2490.3700.2980.2430.2090.1940.2180.2190.2280.2320.2560.1920.1960.1910.2080.1940.1910.1920.2130.2820.3260.2340.3580.1920.2040.2530.2060.2190.2070.2190.2420.2550.2850.3610.3120.2730.3260.2620.3140.1890.2470.2480.1910.2660.2250.1990.1920.1960.1900.2640.1890.1910.2780.3080.2040.2450.2470.0530.0000.0000.0230.0000.1320.0180.0000.0190.1440.0190.0641.0000.0320.0420.0000.0610.0000.2560.1400.0440.0420.0000.0000.0000.0000.0060.0000.0000.0280.0000.013
revenue_Under 100M0.9980.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.1160.0000.0000.0000.0000.0000.0260.0120.0000.0360.0100.0000.0440.0250.0220.0280.0000.0000.0000.0470.0000.0200.0000.0000.0330.0000.0340.0000.3280.3190.3240.3550.3320.3230.3330.3180.3180.3170.3180.3190.3180.3230.3170.3220.3190.3180.3170.3180.3270.3210.3180.3170.3180.3450.3240.3180.3200.3180.3180.3190.3200.3360.3200.3180.3240.3200.3190.3220.3290.3260.3190.3180.3310.3200.3170.3210.3190.3170.3170.3210.3230.3200.3190.3270.3220.3190.3190.3330.3200.3270.3380.3180.3260.3270.3180.3260.3290.3190.3280.3230.3190.3180.3210.3210.3190.3180.3170.3180.3180.3180.3180.3190.3180.3280.3340.3190.3280.3210.3180.3190.3240.3220.3180.3210.3440.3190.3220.3350.3310.3210.3260.3190.3250.3170.3240.3190.3180.3180.3210.3200.3170.3240.3180.3180.3170.3180.3240.3370.3190.3190.3190.0240.0070.0000.0000.0000.0190.0000.0000.0000.0000.0350.0600.0321.0000.0640.0090.0890.0000.3610.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0170.0000.000
revenue_Under 10B0.9980.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0210.0760.0210.1110.0000.0430.0840.0150.2170.0830.0850.0000.0230.0320.0170.0300.0000.1250.0960.0820.0750.0160.2090.0000.2210.1490.0000.3540.3690.3670.4510.3810.3660.3770.3650.3650.3640.3680.3650.3660.3770.3640.3840.3650.3680.3700.3650.3860.3720.3680.3640.3660.4330.3780.3700.3680.3650.3740.3650.3650.4000.3650.3670.3650.3650.3660.3650.3810.3820.3700.3650.3820.4000.3650.3650.3650.3650.3640.3710.3650.3760.3710.3760.3880.3930.3670.3880.3780.3960.3940.3650.3720.3820.3650.3740.3850.3660.3780.3720.3690.3690.3760.3650.3650.3670.3670.3690.3660.3650.3650.3700.3650.3830.4050.3650.3740.3650.3850.3700.3670.3700.3650.3670.4040.3670.3720.3740.3830.3690.3760.3740.3700.3640.3960.3770.3650.3650.3780.3750.3650.3660.3650.3650.3640.3720.3700.3990.3670.3670.3650.0880.0000.0300.0310.0000.1520.0080.0280.0000.1760.0450.1120.0420.0641.0000.0180.1080.0000.4340.0930.0570.0000.0000.0150.0000.0000.0000.0000.0320.0600.0000.000
revenue_Under 10M0.9980.0310.0000.0000.0000.0000.0330.0000.0000.0000.0140.0000.0180.0360.0120.0400.0000.0060.0000.0140.0000.0210.0100.0410.0130.0070.0390.0090.0200.0570.0000.0470.0000.0060.0170.0000.0000.0000.0000.0000.0000.1510.1520.1490.1500.1570.1500.1510.1490.1490.1460.1480.1490.1480.1530.1460.1530.1490.1500.1490.1480.1490.1510.1480.1460.1620.1500.1480.1530.1480.1480.1510.1530.1490.1480.1490.1520.1480.1480.1480.1500.1490.1480.1500.1490.1570.1480.1530.1520.1490.1490.1460.1490.1480.1500.1510.1480.1490.1500.1520.1520.1490.1540.1510.1500.1490.1500.1480.1490.1490.1490.1480.1490.1490.1490.1480.1480.1530.1490.1490.1490.1490.1490.1480.1500.1480.1480.1580.1490.1540.1490.1500.1490.1550.1490.1540.1480.1560.1530.1500.1540.1530.1490.1510.1480.1480.1460.1490.1540.1480.1500.1480.1490.1500.1770.1480.1490.1460.1480.1480.1500.1500.1510.1480.0000.0000.0130.0000.0000.0000.0000.0000.0390.0370.0000.0260.0000.0090.0181.0000.0330.0000.1570.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0140.0000.000
revenue_Under 1B0.9980.0480.0000.0000.0000.0280.0180.0130.0200.0000.0230.0000.0080.0650.0350.0650.0360.0370.0590.0390.0420.0340.0620.0710.0630.0560.0290.0310.0620.0410.0500.0320.0960.0420.1130.0290.1680.0060.1750.1330.0300.4760.4770.4780.4840.4810.4750.4780.4750.4740.4720.4730.4730.4740.4810.4720.4820.4730.4730.4770.4740.4800.4740.4740.4720.4730.4790.4840.4730.4740.4730.4750.4740.4770.4910.4750.4750.4730.4740.4760.4770.4740.4730.4780.4740.4910.4830.4800.4740.4730.4730.4720.4770.4750.4760.4790.4780.4880.4860.4730.4800.4800.4810.4790.4740.4810.4780.4770.4800.4790.4740.4900.4820.4760.4770.4800.4760.4790.4730.4770.4750.4810.4730.4740.4780.4730.4860.4860.4740.4830.4760.4770.4800.4760.4740.4730.4780.4740.4780.4840.4860.4800.4800.4810.4810.4760.4720.4920.4800.4730.4800.4860.4750.4730.4730.4740.4760.4720.4740.4770.4820.4740.4800.4790.0560.0920.0410.0330.0000.0270.0000.0000.0000.1190.0650.1140.0610.0890.1080.0331.0000.0000.5890.0740.0570.0130.0080.0040.0000.0000.0370.0010.0290.0330.0050.000
revenue_Under 1M0.9980.0430.0000.0000.0000.0000.0000.0100.0000.0000.0000.0270.0330.0000.0000.0060.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0450.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0620.0660.0670.0770.0710.0650.0700.0650.0650.0600.0640.0650.0640.0690.0600.0690.0640.0650.0650.0640.0700.0650.0640.0600.0690.0670.0800.0660.0660.0640.1090.0650.0650.0750.0650.0650.0640.0640.0660.0650.0780.0760.0670.0690.0780.0700.0650.0660.0670.0640.0600.0690.0680.0690.0870.0830.0830.0700.0660.0690.0720.0810.0670.0650.0650.0650.0660.0650.0740.0640.0730.0990.0740.0810.0640.0680.0660.0650.0640.0640.0680.0640.0640.0650.0640.0700.0680.0640.0700.0690.1060.0730.0640.0700.0660.0660.0840.0670.0650.0650.0660.0680.0720.0670.0710.0600.0700.0670.0640.0660.0810.0680.0690.0640.0640.0650.0600.0640.0680.0730.0650.0650.0660.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0650.0000.0250.0000.0000.0000.0000.0000.0000.0320.0000.0000.0000.000
revenue_nan1.0000.0370.0050.0000.0000.0000.0000.0000.0100.0000.0290.0020.0340.1240.0490.1220.0550.1310.0550.0600.1270.0500.2400.1270.1160.0310.0750.0290.0830.0460.0360.1840.2160.1470.1540.0650.3620.0000.3390.2350.0270.8210.8260.8250.8290.8260.8250.8260.8250.8250.8250.8250.8250.8250.8260.8250.8260.8250.8250.8250.8250.8260.8250.8250.8250.8250.8300.8250.8250.8250.8250.8260.8250.8250.8270.8250.8250.8250.8250.8250.8250.8260.8260.8260.8260.8250.8270.8270.8250.8260.8260.8250.8250.8250.8260.8250.8250.8250.8260.8260.8250.8270.8280.8280.8250.8270.8280.8250.8280.8270.8250.8260.8270.8250.8250.8250.8250.8250.8250.8250.8250.8250.8250.8260.8260.8250.8250.8270.8250.8260.8280.8260.8250.8270.8260.8250.8250.8270.8250.8250.8250.8260.8250.8260.8260.8270.8250.8250.8260.8250.8250.8250.8260.8250.8250.8250.8250.8250.8250.8260.8270.8250.8250.8250.0940.0680.0560.0540.0000.1450.0000.0330.0000.1960.1150.2150.2560.3610.4340.1570.5890.0651.0000.1120.0850.0310.0170.0080.0000.0110.0260.0300.0500.0530.0000.000
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state_top_CA0.0630.3510.0890.0300.0940.0790.0660.1460.0340.0000.0570.1760.3530.1500.0430.0590.0500.0530.0540.0870.0440.0840.0640.0430.0820.1200.0440.1360.0490.1220.0430.0510.0600.0510.0530.0500.0540.0730.0830.1270.0450.0510.0360.0360.0380.0370.0350.0430.0350.0350.0380.0360.0410.0370.0350.0380.0350.0350.0350.0380.0490.0400.0350.0380.0380.0580.0380.0920.0350.0360.0370.0790.0420.0360.0350.0350.0370.0360.0370.0350.0370.0770.0750.0410.0510.0470.0650.1290.0830.0560.0450.0380.0670.0640.0350.1150.0880.0660.0910.0380.0500.0370.0360.0350.0350.0470.0350.0490.0350.0580.0380.0510.0650.0360.0630.0520.0350.0370.0380.0580.0410.0660.0360.0400.0380.0490.0410.0370.0410.0370.0880.0710.0380.1300.0580.0460.0410.0440.0430.0450.0430.0360.0410.0440.0420.0460.0380.0770.0350.0370.0540.0650.1540.0790.0790.0360.0350.0380.0370.0430.0350.0350.0460.0390.0520.0840.0360.0210.0000.0000.0090.0000.0390.1100.0150.0280.0420.0000.0000.0000.0130.0000.0310.9900.9991.0000.0660.0700.0530.0830.0970.3590.1790.2310.1030.066
state_top_CO0.0000.0800.0080.0000.0110.0000.0000.0320.0000.0000.0000.0420.0930.0000.0000.0000.0000.0000.0000.0000.0000.0240.0530.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0290.0000.0000.0120.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0340.0140.0000.0000.0270.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0320.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0180.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0430.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0350.0000.0000.0230.0420.0000.0140.0000.0000.0000.0000.0080.0000.0170.9900.9990.0661.0000.0000.0000.0000.0130.0940.0430.0580.0160.000
state_top_FL0.0630.0860.0120.0000.0140.0020.0000.0350.0000.0000.0000.0450.0980.0340.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0160.0000.0000.0190.0000.0290.0000.0000.0620.0130.0760.0000.0000.0000.0000.0000.0000.0340.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0090.0000.0000.0130.0000.0270.0000.0000.0000.0230.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0150.0310.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0140.0000.0000.0000.0000.0110.0220.0000.0380.0340.0270.0000.0000.0150.0000.0040.0000.0080.9900.9990.0700.0001.0000.0000.0070.0160.1000.0460.0620.0190.000
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state_top_Other0.1090.3110.0780.0240.0820.0690.0570.1290.0280.0000.0490.1560.3140.0520.0240.0500.0270.0240.0490.0340.0660.0250.0230.0460.0560.0350.0320.0970.0290.0640.0530.0230.0270.0380.0350.0340.1970.1430.0770.0820.0270.0350.0390.0430.0740.0450.0380.0630.0540.0380.0410.0390.0390.0420.0720.0410.0580.0410.0380.0610.0390.0720.0760.0530.0410.0450.0680.0550.0380.0420.0420.0970.0390.0420.0410.0410.0380.0390.0420.0430.0390.0510.0740.0430.0380.0650.0670.0410.0460.0410.0440.0410.0410.0390.0440.0470.0410.0480.0450.0400.0560.0450.0710.0530.0460.0900.0670.0380.0720.0510.0380.0440.0560.0450.0390.0400.0380.0490.0380.0510.0430.0380.0420.0400.0380.0390.0400.0760.0390.0810.0490.0580.0400.0380.0380.0380.0410.1180.0510.0530.0710.0770.0630.0580.0720.0620.0410.0500.0510.0400.0380.0650.0380.0470.0400.0390.0450.0410.0420.0560.0540.0390.0490.0490.0610.0000.0100.0270.0040.0770.0410.0000.0330.1110.0000.0320.0280.0170.0600.0140.0330.0000.0530.9900.9990.2310.0580.0620.0460.0730.0860.3190.1591.0000.0910.058
state_top_TX0.0270.1340.0290.0000.0310.0230.0160.0550.0000.0000.0090.0680.1420.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.0290.0000.0400.0000.0000.0140.0040.0000.0000.0050.0000.0000.0000.0060.0000.0000.0000.0000.0060.0000.0000.0190.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0290.0140.0000.0000.0060.0000.0000.0000.0230.0110.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0330.0110.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0100.0060.0000.0000.0000.0120.0000.0000.0000.0040.0000.0000.0060.0540.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0130.0000.0000.0000.0090.0000.0000.0000.0000.0050.0000.0000.9900.9990.1030.0160.0190.0040.0260.0330.1440.0690.0911.0000.016
state_top_WA0.0000.0800.0080.0000.0110.0000.0000.0320.0000.0000.0000.0420.0930.0000.0000.0760.0000.0000.0000.0000.0000.0080.0640.0000.0370.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0510.0190.0310.0000.0000.0230.0210.0360.0000.0130.0390.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0430.0000.0000.0190.0000.0000.0000.0280.0000.0190.0160.0000.0000.0290.0000.0630.0000.0710.0000.0000.0000.0000.0080.0340.0250.0000.0000.0000.0000.0190.0450.0000.0000.0000.0430.0210.0000.0190.0350.0170.0000.0000.0210.0340.0110.0060.0000.0100.0410.0690.0070.0260.0000.0080.0000.0000.0000.0010.0000.0180.0000.0000.0490.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0300.0000.0220.0000.0200.0260.0430.0000.0230.0120.0180.0360.0230.0000.0130.0000.0000.0000.0000.0000.0180.0000.0020.0000.0000.0460.0000.0000.0230.0000.0000.0650.0590.0000.0040.0000.0130.0570.0000.0180.0150.0180.0690.0000.0000.0130.0000.0000.0000.0000.0000.0000.9900.9990.0660.0000.0000.0000.0000.0130.0940.0430.0580.0161.000

Missing values

2023-12-31T13:50:59.110968image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-31T13:51:00.202363image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-31T13:51:01.174617image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

account_idis_current_customeris_self_serviceis_arr_over_12kcompany_revenue_bucketcountrystateindustry_groupedhas_crossbeam_datacrossbeam_product1_customercrossbeam_product2_customercrossbeam_product3_customercrossbeam_product4_customercrossbeam_product5_customercrossbeam_product6_customercrossbeam_product7_customercrossbeam_product8_customercrossbeam_product9_customercrossbeam_product10_customercrossbeam_product11_customercrossbeam_product12_customercrossbeam_product13_customercrossbeam_product14_customercrossbeam_product15_customercrossbeam_product16_customercrossbeam_product17_customercrossbeam_product18_customercrossbeam_product19_customercrossbeam_product20_customercrossbeam_product21_customercrossbeam_product22_customercrossbeam_product23_customerdnb_founded_time_groupedhas_hg_datahg_product_27hg_product_28hg_product_29hg_product_30hg_product_31hg_product_32hg_product_33hg_product_34hg_product_35hg_product_36hg_product_37hg_product_38hg_product_39hg_product_40hg_product_41hg_product_42hg_product_43hg_product_44hg_product_45hg_product_46hg_product_47hg_product_48hg_product_49hg_product_50hg_product_51hg_product_52hg_product_53hg_product_54hg_product_55hg_product_56hg_product_57hg_product_58hg_product_59hg_product_60hg_product_61hg_product_62hg_product_63hg_product_64hg_product_65hg_product_66hg_product_67hg_product_68hg_product_69hg_product_70hg_product_71hg_product_72hg_product_73hg_product_74hg_product_75hg_product_76hg_product_77hg_product_78hg_product_79hg_product_80hg_product_81hg_product_82hg_product_83hg_product_84hg_product_85hg_product_86hg_product_87hg_product_88hg_product_89hg_product_90hg_product_91hg_product_92hg_product_93hg_product_94hg_product_95hg_product_96hg_product_97hg_product_98hg_product_99hg_product_100hg_product_101hg_product_102hg_product_103hg_product_104hg_product_105hg_product_106hg_product_107hg_product_108hg_product_109hg_product_110hg_product_111hg_product_112hg_product_113hg_product_114hg_product_115hg_product_116hg_product_117hg_product_118hg_product_119hg_product_120hg_product_121hg_product_122hg_product_123hg_product_124hg_product_125hg_product_126hg_product_127hg_product_128hg_product_129hg_product_130hg_product_131hg_product_132hg_product_133hg_product_134hg_product_135hg_product_136hg_product_137hg_product_138hg_product_139hg_product_140hg_product_141hg_product_142hg_product_143hg_product_144hg_product_145hg_product_146hg_product_147hg_product_148country_topstate_topcountry_top_AUcountry_top_BRcountry_top_CAcountry_top_DEcountry_top_FRcountry_top_GBcountry_top_INcountry_top_Missingcountry_top_NLcountry_top_Othercountry_top_USstate_top_CAstate_top_COstate_top_FLstate_top_GAstate_top_ILstate_top_MAstate_top_Missingstate_top_NYstate_top_Otherstate_top_TXstate_top_WAindustry_1. Tech - Computer systems design and related servicesindustry_2. Tech - Software Publisherindustry_3. Financeindustry_4. Consultingindustry_5. Retailindustry_6. Manufacturingindustry_7. Wholesale Tradeindustry_8. Healthcareindustry_9. Otherindustry_nanrevenue_Over 10Brevenue_Under 100Mrevenue_Under 10Brevenue_Under 10Mrevenue_Under 1Brevenue_Under 1Mrevenue_nanfounded_After 2000founded_Before 2000founded_nan
58130011G00000tL14IQASTrue1.01.0NaNAGNaN9. OtherFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0OtherMissingFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
61600011G00000gY7jaQACTrue-1.01.0NaNFRNaN2. Tech - Software PublisherFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0After 2000False0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0FRMissingFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalse
62670011G00000kx074QAATrue-1.01.0NaNUSCANaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0USCAFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
104770011G00000pPUQ1QAOTrue-1.01.0NaNUSNE3. FinanceFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0Before 2000False0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0USOtherFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalse
172040013700000YPwoTAATTrue1.01.0NaNDENaN1. Tech - Computer systems design and related servicesFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0After 2000False0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0DEMissingFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalse
207820011G00000kwwQdQAITrue1.01.0NaNUSMI1. Tech - Computer systems design and related servicesFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0USOtherFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
212530011G00000uns5zQAATrue1.01.0NaNNLNaN9. OtherFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NLMissingFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
227290011G00000ugvn9QAATrue1.01.0NaNGBNaNNaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0GBMissingFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
358320011G00000kBsCcQAKTrue-1.01.0NaNUSNY9. OtherFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0USNYFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
365140011G00000kuqW4QAITrue1.01.0NaNGBNaN9. OtherFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNFalse0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0GBMissingFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrue
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5095110011G00000gXqJjQAKTrue-1.01.0Under 1BCANaN9. OtherTrue-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.01.0Before 2000True-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.01.01.01.0-1.01.0-1.0-1.0-1.0-1.0-1.01.01.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.01.0-1.01.01.0-1.01.0-1.0CAMissingFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseTrueFalse
5095210013700000UtJ3rAAFTrue-1.01.0Under 1BUSCA5. RetailTrue-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.01.0After 2000True-1.01.0-1.0-1.01.0-1.01.01.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.0-1.0-1.0-1.01.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.0-1.01.01.0-1.0-1.0-1.01.01.0-1.01.0-1.0USCAFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalse
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